Publications

Evaluating retrieval-augmented generation versus long-context input for clinical reasoning over electronic health records

Published in Journal of the American Medical Informatics Association, 2026

Recommended citation:

Skatje Myers, Dmitriy Dligach, Timothy A Miller, Samantha Barr, James Landefeld, Yanjun Gao, Matthew M Churpek, Anoop Mayampurath, and Majid Afshar. 2026. Evaluating retrieval-augmented generation versus long-context input for clinical reasoning over electronic health records. In Journal of the American Medical Informatics Association.

Natural language processing to build a computable phenotype library for adults with congenital heart disease

Published in International Journal of Medical Informatics, 2026

Recommended citation:

Spencer Thomas, Angus Dawson, Hifsa Chaudhry, Sidra Ahmad, Xiyu Ding, Sarah A Hummel, David M Leone, Rohith Vanam, Angela J Weingarten, Eric Farber-Eger, Lauren Lee Shaffer, Benjamin P Frischhertz, Sydney St Clemmons, Sunil J Ghelani, Fernando Baraona Reyes, Tzu-Chun Wu, Danny TY Wu, Alexander R Opotowsky, and Timothy A Miller. 2026. Natural language processing to build a computable phenotype library for adults with congenital heart disease. In International Journal of Medical Informatics. https://www.sciencedirect.com/science/article/pii/S1386505626004144

Robust AI-ECG for Predicting Left Ventricular Systolic Dysfunction in Pediatric Congenital Heart Disease

Published in AMIA Summits on Translational Science Proceedings, 2026

Recommended citation:

Yuting Yang, Lorenzo Peracchio, Joshua Mayourian, John K Triedman, Timothy Miller, and William G La Cava. 2026. Robust AI-ECG for Predicting Left Ventricular Systolic Dysfunction in Pediatric Congenital Heart Disease. In AMIA Summits on Translational Science Proceedings. https://pmc.ncbi.nlm.nih.gov/articles/PMC13274275/

Comparing prognostic performance and reasoning between physicians and large language models

Published in Journal of Pain and Symptom Management, 2026

Recommended citation:

Megan Gjertsen, WonJin Yoon, Majid Afshar, Emma Croxford, John R Caskey, Yanjun Gao, Timothy A Miller, and Jacqueline M Kruser. 2026. Comparing prognostic performance and reasoning between physicians and large language models. In Journal of Pain and Symptom Management. https://www.jpsmjournal.com/article/S0885-3924(26)00333-7/fulltext

Pediatric Sepsis Cohort Detection Using In-Context Pointwise r-Usable Information

Published in The 8th Workshop on Clinical Natural Language Processing (Clinical NLP)@ LREC 2026, 2026

Recommended citation:

Yingya Li, Alon Geva, Steven Bethard, Timothy Miller, Kate Madden, Matthew Eisenberg, Daniel Kelly, and Guergana Savova. 2026. Pediatric Sepsis Cohort Detection Using In-Context Pointwise r-Usable Information. In The 8th Workshop on Clinical Natural Language Processing (Clinical NLP)@ LREC 2026. https://aclanthology.org/2026.clinicalnlp-1.pdf#page=352

Automated Echocardiographic Detection of Congenital Heart Disease Using Artificial Intelligence

Published in Circulation, 2026

Recommended citation:

Platon Lukyanenko, Sunil J Ghelani, Yuting Yang, Bohan Jiang, Timothy A Miller, David Harrild, Nao Sasaki, Francesca Sperotto, Danielle Sganga, John K Triedman, Andrew J Powell, Tal Geva, William G La Cava, and Joshua Mayourian. 2026. Automated Echocardiographic Detection of Congenital Heart Disease Using Artificial Intelligence. In Circulation. https://www.ahajournals.org/doi/full/10.1161/CIRCULATIONAHA.126.079781

A Dataset of Psychiatric Hospital Notes with Temporal Information Annotations

Published in LREC... International Conference on Language Resources & Evaluation:[proceedings]. International Conference on Language Resources & Evaluation, 2026

Recommended citation:

Timothy Miller, Gaby Dinh, David Harris, WonJin Yoon, Spencer Thomas, Boyu Ren, Mei-Hua Hall, and Guergana Savova. 2026. A Dataset of Psychiatric Hospital Notes with Temporal Information Annotations. In LREC... International Conference on Language Resources & Evaluation:[proceedings]. International Conference on Language Resources & Evaluation. https://aclanthology.org/anthology-files/anthology-files/pdf/lrec/2026.lrec-1.592.pdf

Comparing prognostic performance and reasoning between large language models and physicians

Published in medRxiv, 2026

Recommended citation:

Megan Gjertsen, WonJin Yoon, Majid Afshar, Brandon Temte, Brandon Leding, Stephen Halliday, Kaitlin Bradley, Joseph Kim, Juliana Mitchell, Anna K Sanders, Emma Croxford, John Caskey, Matthew Churpek, Anoop Mayampurath, Yanjun Gao, Timothy Miller, and Jacqueline M Kruser. 2026. Comparing prognostic performance and reasoning between large language models and physicians. In medRxiv. https://www.medrxiv.org/content/medrxiv/early/2026/04/25/2026.04.17.26350898.full.pdf

Deep Learning-Based Automated Echocardiographic Measurements in Pediatric and Congenital Heart Disease

Published in medRxiv, 2026

Recommended citation:

Platon Lukyanenko, Sunil Ghelani, Yuting Yang, Bohan Jiang, Timothy Miller, Peter Higgins, Manouk Kirakosian, Kaitlyn Tracy, Janet Kane, David Harrild, John Triedman, Andrew J Powell, Tal Geva, William G La Cava, and Joshua Mayourian. 2026. Deep Learning-Based Automated Echocardiographic Measurements in Pediatric and Congenital Heart Disease. In medRxiv. https://pmc.ncbi.nlm.nih.gov/articles/PMC12919117/

Toward Digital Twins in the Intensive Care Unit: A Medication Management Case Study

Published in , 2026

Recommended citation:

MS Behnaz Eslami, Majid Afshar, Timothy Miller, Matthew Churpek, Yanjun Gao, and Dmitriy Dligach. 2026. Toward Digital Twins in the Intensive Care Unit: A Medication Management Case Study. https://www.researchgate.net/profile/Behnaz-Eslami/publication/387494424_Toward_Digital_Twins_in_the_Intensive_Care_Unit_A_Medication_Management_Case_Study/links/68b1cc4eca495d7698313332/Toward-Digital-Twins-in-the-Intensive-Care-Unit-A-Medication-Management-Case-Study.pdf

Aspect-oriented summarization for psychiatric short-term readmission prediction

Published in Proceedings of the 2025 Conference on Empirical Methods in Natural Language …, 2025, 2025

Recommended citation:

WonJin Yoon, Boyu Ren, Spencer Thomas, Chanhwi Kim, Guergana K Savova, Mei-Hua Hall, and Timothy A Miller. 2025. Aspect-oriented summarization for psychiatric short-term readmission prediction. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language …, 2025. https://aclanthology.org/2025.emnlp-main.1423.pdf

Natural Language Processing to Build a Multicenter Computable Phenotype Library for Adults with Congenital Heart Disease

Published in medRxiv, 2025

Recommended citation:

Spencer Thomas, Angus Dawson, Hifsa Chaudhry, Sidra Ahmad, Xiyu Ding, Sarah A Hummel, David M Leone, Angela J Weingarten, Eric Farber-Eger, Lauren Lee Shaffer, Benjamin P Frischhertz, Sydney St. Clemmons, Sunil J Ghelani, Fernando Baraona Reyes, Tzu-Chun Wu, Danny TY Wu, Alexander R Opotowsky, and Timothy A Miller. 2025. Natural Language Processing to Build a Multicenter Computable Phenotype Library for Adults with Congenital Heart Disease. In medRxiv. https://www.medrxiv.org/content/10.1101/2025.08.18.25331953.full.pdf

Loyola at ArchEHR-QA 2025: Exploring Unsupervised Attribution of Generated Text: Attention and Clustering-Based Methods

Published in Proceedings of the 24th Workshop on Biomedical Language Processing (Shared Tasks), 2025

Recommended citation:

Rohan Sethi, Timothy Miller, Majid Afshar, and Dmitriy Dligach. 2025. Loyola at ArchEHR-QA 2025: Exploring Unsupervised Attribution of Generated Text: Attention and Clustering-Based Methods. In Proceedings of the 24th Workshop on Biomedical Language Processing (Shared Tasks), pages 22–26, Vienna, Austria. Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.bionlp-share.3

대형 언어 모델을 활용한 연구를 위한 TRIPOD-LLM 보고 지침

Published in Ewha medical journal, 2025

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Jack Gallifant, Majid Afshar, Saleem Ameen, Yindalon Aphinyanaphongs, Shan Chen, Giovanni Cacciamani, Dina Demner-Fushman, Dmitriy Dligach, Roxana Daneshjou, Chrystinne Fernandes, Lasse Hyldig Hansen, Adam Landman, Lisa Lehmann, Liam G McCoy, Timothy Miller, Amy Moreno, Nikolaj Munch, David Restrepo, Guergana Savova, Renato Umeton, Judy Wawira Gichoya, Gary S Collins, Karel GM Moons, Leo A Celi, and Danielle S Bitterman. 2025. 대형 언어 모델을 활용한 연구를 위한 TRIPOD-LLM 보고 지침. In Ewha medical journal.

Do They Really Know? Evaluating Large Language Models’ Ability to Reference and Cite Oncology Guidelines

Published in International Conference on Artificial Intelligence in Medicine, 2025

Recommended citation:

Belligoli, P., Bitterman, D., Miller, T. (2025). Do They Really Know? Evaluating Large Language Models’ Ability to Reference and Cite Oncology Guidelines. In: Bellazzi, R., Juarez Herrero, J.M., Sacchi, L., Zupan, B. (eds) Artificial Intelligence in Medicine. AIME 2025. Lecture Notes in Computer Science(), vol 15735. Springer, Cham. https://doi.org/10.1007/978-3-031-95841-0_6 https://doi.org/10.1007/978-3-031-95841-0_6

Uncertainty estimation in diagnosis generation from large language models: next-word probability is not pre-test probability

Published in JAMIA Open, 2025

Recommended citation:

Yanjun Gao, Skatje Myers, Shan Chen, Dmitriy Dligach, Timothy Miller, Danielle S Bitterman, Guanhua Chen, Anoop Mayampurath, Matthew M Churpek, Majid Afshar, Uncertainty estimation in diagnosis generation from large language models: next-word probability is not pre-test probability, JAMIA Open, Volume 8, Issue 1, February 2025, ooae154, https://doi.org/10.1093/jamiaopen/ooae154 https://doi.org/10.1093/jamiaopen/ooae154

Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies

Published in JAMIA, 2024

Recommended citation:

Skatje Myers, Timothy A Miller, Yanjun Gao, Matthew M Churpek, Anoop Mayampurath, Dmitriy Dligach, Majid Afshar, Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies, Journal of the American Medical Informatics Association, Volume 32, Issue 2, February 2025, Pages 357–364, https://doi.org/10.1093/jamia/ocae308 https://doi.org/10.1093/jamia/ocae308

LCD benchmark: long clinical document benchmark on mortality prediction for language models

Published in Journal of the American Medical Informatics Association, 2024

Recommended citation:

WonJin Yoon, Shan Chen, Yanjun Gao, Zhanzhan Zhao, Dmitriy Dligach, Danielle S Bitterman, Majid Afshar, Timothy Miller, LCD benchmark: long clinical document benchmark on mortality prediction for language models. Journal of the American Medical Informatics Association, 2024, ocae287, https://doi.org/10.1093/jamia/ocae287 https://doi.org/10.1093/jamia/ocae287

When raw data prevails: Are large language model embeddings effective in numerical data representation for medical machine learning applications?

Published in Findings of the Association for Computational Linguistics: EMNLP 2024, 5414-5428, 2024, 2024

Recommended citation:

Yanjun Gao, Skatje Myers, Shan Chen, Dmitriy Dligach, Timothy A Miller, Danielle Bitterman, Matthew Churpek, and Majid Afshar. 2024. When raw data prevails: Are large language model embeddings effective in numerical data representation for medical machine learning applications?. In Findings of the Association for Computational Linguistics: EMNLP 2024, 5414-5428, 2024. https://aclanthology.org/2024.findings-emnlp.311.pdf

The TRIPOD-LLM statement: a targeted guideline for reporting large language models use

Published in Medrxiv, 2024

Recommended citation:

Jack Gallifant, Majid Afshar, Saleem Ameen, Yindalon Aphinyanaphongs, Shan Chen, Giovanni Cacciamani, Dina Demner-Fushman, Dmitriy Dligach, Roxana Daneshjou, Chrystinne Fernandes, Lasse Hyldig Hansen, Adam Landman, Lisa Lehmann, Liam G McCoy, Timothy Miller, Amy Moreno, Nikolaj Munch, David Restrepo, Guergana Savova, Renato Umeton, Judy Wawira Gichoya, Gary S Collins, Karel GM Moons, Leo A Celi, and Danielle S Bitterman. 2024. The TRIPOD-LLM statement: a targeted guideline for reporting large language models use. In Medrxiv. https://www.medrxiv.org/content/10.1101/2024.07.24.24310930.full.pdf

Cumulus: a federated electronic health record-based learning system powered by Fast Healthcare Interoperability Resources and artificial intelligence

Published in Journal of the American Medical Informatics Association, 2024

Recommended citation:

Andrew J McMurry, Daniel I Gottlieb, Timothy A Miller, James R Jones, Ashish Atreja, Jennifer Crago, Pankaja M Desai, Brian E Dixon, Matthew Garber, Vladimir Ignatov, Lyndsey A Kirchner, Philip R O Payne, Anil J Saldanha, Prabhu R V Shankar, Yauheni V Solad, Elizabeth A Sprouse, Michael Terry, Adam B Wilcox, Kenneth D Mandl, Cumulus: a federated electronic health record-based learning system powered by Fast Healthcare Interoperability Resources and artificial intelligence, Journal of the American Medical Informatics Association, Volume 31, Issue 8, August 2024, Pages 1638–1647, https://doi.org/10.1093/jamia/ocae130 https://doi.org/10.1093/jamia/ocae130

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models

Published in JAMIA, 2024

Recommended citation:

Jifan Gao, Guanhua Chen, Ann P O’Rourke, John Caskey, Kyle A Carey, Madeline Oguss, Anne Stey, Dmitriy Dligach, Timothy Miller, Anoop Mayampurath, Matthew M Churpek, Majid Afshar, Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models, Journal of the American Medical Informatics Association, Volume 31, Issue 6, June 2024, Pages 1291–1302, https://doi.org/10.1093/jamia/ocae071 https://doi.org/10.1093/jamia/ocae071

Development of a Benchmark Corpus for Medical Device Adverse Event Detection

Published in CL4Health Workshop, 2024

Recommended citation:

Susmitha Wunnava, David A. Harris, Florence T. Bourgeois, and Timothy A. Miller. 2024. Development of a Benchmark Corpus for Medical Device Adverse Event Detection. In Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024, pages 240–245, Torino, Italia. ELRA and ICCL. https://aclanthology.org/2024.cl4health-1.29

Standardizing Multi-site Clinical Note Titles to LOINC Document Ontology: A Transformer-based Approach

Published in AMIA Annual Symposium Proceedings, 2024

Recommended citation:

Xu Zuo, Yujia Zhou, Jon Duke, George Hripcsak, Nigam Shah, Juan M Banda, Ruth Reeves, Timothy Miller, Lemuel R Waitman, Karthik Natarajan, and Hua Xu. 2024. Standardizing Multi-site Clinical Note Titles to LOINC Document Ontology: A Transformer-based Approach. In AMIA Annual Symposium Proceedings. https://pmc.ncbi.nlm.nih.gov/articles/PMC10785935/

Improving Model Transferability for Clinical Note Section Classification Models Using Continued Pretraining

Published in Journal of the American Medical Informatics Association (JAMIA), 2023

Recommended citation:

Weipeng Zhou, Meliha Yetisgen, Yanjun Gao, Guergana Savova, and Timothy Miller. 2023. Improving Model Transferability for Clinical Note Section Classification Models Using Continued Pretraining. JAMIA, September 2023, ocad190 https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocad190/7277369?login=true

An end-to-end natural language processing system for automatically extracting radiation therapy events from clinical texts

Published in International Journal of Radiation Oncology* Biology* Physics, 2023

Recommended citation:

Danielle S Bitterman, Eli Goldner, Sean Finan, David Harris, Eric B Durbin, Harry Hochheiser, Jeremy L Warner, Raymond H Mak, Timothy Miller, and Guergana K Savova. 2023. An end-to-end natural language processing system for automatically extracting radiation therapy events from clinical texts. In International Journal of Radiation Oncology* Biology* Physics. https://www.sciencedirect.com/science/article/am/pii/S036030162300295X

Improving the Transferability of Clinical Note Section Classification Models with BERT and Large Language Model Ensembles

Published in Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023

Recommended citation:

Weipeng Zhou, Majid Afshar, Dmitriy Dligach, Yanjun Gao, and Timothy Miller. 2023. Improving the Transferability of Clinical Note Section Classification Models with BERT and Large Language Model Ensembles. In Proceedings of the 5th Clinical Natural Language Processing Workshop, pages 125–130, Toronto, Canada. Association for Computational Linguistics. https://aclanthology.org/2023.clinicalnlp-1.16/

Two-Stage Fine-Tuning for Improved Bias and Variance for Large Pretrained Language Models

Published in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Recommended citation:

Lijing Wang, Yingya Li, Timothy Miller, Steven Bethard, and Guergana Savova. 2023. Two-Stage Fine-Tuning for Improved Bias and Variance for Large Pretrained Language Models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 15746–15761, Toronto, Canada. Association for Computational Linguistics. https://aclanthology.org/2023.acl-long.877/

Overview of the problem list summarization (probsum) 2023 shared task on summarizing patients’ active diagnoses and problems from electronic health record progress notes

Published in Proceedings of the 22nd Workshop on Biomedical Natural Language Processing …, 2023, 2023

Recommended citation:

Yanjun Gao, Dmitriy Dligach, Timothy A Miller, and Majid Afshar. 2023. Overview of the problem list summarization (probsum) 2023 shared task on summarizing patients’ active diagnoses and problems from electronic health record progress notes. In Proceedings of the 22nd Workshop on Biomedical Natural Language Processing …, 2023. https://aclanthology.org/2023.bionlp-1.43.pdf

Natural language processing to automatically extract the presence and severity of esophagitis in notes of patients undergoing radiotherapy

Published in JCO Clinical Cancer Informatics, 2023

Recommended citation:

Shan Chen, Marco Guevara, Nicolas Ramirez, Arpi Murray, Jeremy L Warner, Hugo JWL Aerts, Timothy A Miller, Guergana K Savova, Raymond H Mak, and Danielle S Bitterman. 2023. Natural language processing to automatically extract the presence and severity of esophagitis in notes of patients undergoing radiotherapy. In JCO Clinical Cancer Informatics. https://arxiv.org/pdf/2303.13722

Multi-task training with in-domain language models for diagnostic reasoning

Published in Proceedings of the 5th Clinical Natural Language Processing Workshop, 78-85, 2023, 2023

Recommended citation:

Brihat Sharma, Yanjun Gao, Timothy A Miller, Matthew Churpek, Majid Afshar, and Dmitriy Dligach. 2023. Multi-task training with in-domain language models for diagnostic reasoning. In Proceedings of the 5th Clinical Natural Language Processing Workshop, 78-85, 2023. https://aclanthology.org/2023.clinicalnlp-1.10.pdf

End-to-end clinical temporal information extraction with multi-head attention

Published in The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, 2023

Recommended citation:

Timothy Miller, Steven Bethard, Dmitriy Dligach, and Guergana Savova. 2023. End-to-end clinical temporal information extraction with multi-head attention. In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 313–319, Toronto, Canada. Association for Computational Linguistics. https://aclanthology.org/2023.bionlp-1.28/

Progress note understanding—assessment and plan reasoning: overview of the 2022 N2C2 track 3 shared task

Published in Journal of biomedical informatics 142, 104346, 2023, 2023

Recommended citation:

Yanjun Gao, Dmitriy Dligach, Timothy Miller, Matthew M Churpek, Ozlem Uzuner, and Majid Afshar. 2023. Progress note understanding—assessment and plan reasoning: overview of the 2022 N2C2 track 3 shared task. In Journal of biomedical informatics 142, 104346, 2023. https://www.sciencedirect.com/science/article/pii/S1532046423000679

Representing and utilizing clinical textual data for real world studies: An OHDSI approach

Published in Journal of Biomedical Informatics, 2023

Recommended citation:

Vipina K. Keloth, Juan M. Banda, Michael Gurley, Paul M. Heider, Georgina Kennedy, Hongfang Liu, Feifan Liu, Timothy Miller, Karthik Natarajan, Olga V Patterson, Yifan Peng, Kalpana Raja, Ruth M. Reeves, Masoud Rouhizadeh, Jianlin Shi, Xiaoyan Wang, Yanshan Wang, Wei-Qi Wei, Andrew E. Williams, Rui Zhang, Rimma Belenkaya, Christian Reich, Clair Blacketer, Patrick Ryan, George Hripcsak, Noémie Elhadad, Hua Xu, Representing and utilizing clinical textual data for real world studies: An OHDSI approach, Journal of Biomedical Informatics, Volume 142, 2023 https://doi.org/10.1016/j.jbi.2023.104343

Natural Language Processing Methods to Empirically Explore Social Contexts and Needs in Cancer Patient Notes

Published in JCO Clinical Cancer Informatics, 2023

Recommended citation:

Natural Language Processing Methods to Empirically Explore Social Contexts and Needs in Cancer Patient Notes. Abigail Derton, Marco Guevara, Shan Chen, Shalini Moningi, David E. Kozono, Dianbo Liu, Timothy A. Miller, Guergana K. Savova, Raymond H. Mak, and Danielle S. Bitterman. JCO Clinical Cancer Informatics 2023 :7

Automatic extraction of medication mentions from tweets—overview of the biocreative VII shared task 3 competition

Published in Database 2023, baac108, 2023, 2023

Recommended citation:

Davy Weissenbacher, Karen O’Connor, Siddharth Rawal, Yu Zhang, Richard Tzong-Han Tsai, Timothy Miller, Dongfang Xu, Carol Anderson, Bo Liu, Qing Han, Jinfeng Zhang, Igor Kulev, Berkay Köprü, Raul Rodriguez-Esteban, Elif Ozkirimli, Ammer Ayach, Roland Roller, Stephen Piccolo, Peijin Han, VG Vinod Vydiswaran, Ramya Tekumalla, Juan M Banda, Parsa Bagherzadeh, Sabine Bergler, João F Silva, Tiago Almeida, Paloma Martinez, Renzo Rivera-Zavala, Chen-Kai Wang, Hong-Jie Dai, Luis Alberto Robles Hernandez, and Graciela Gonzalez-Hernandez. 2023. Automatic extraction of medication mentions from tweets—overview of the biocreative VII shared task 3 competition. In Database 2023, baac108, 2023. https://academic.oup.com/database/article/doi/10.1093/database/baac108/7025388

Exploring methods to understand cancer disparities using natural language processing of clinical notes

Published in International Journal of Radiation Oncology, Biology, Physics, 2022

Recommended citation:

A Derton, A Murray, D Liu, RH Mak, TA Miller, GK Savova, and DS Bitterman. 2022. Exploring methods to understand cancer disparities using natural language processing of clinical notes. In International Journal of Radiation Oncology, Biology, Physics. https://www.redjournal.org/article/S0360-3016(22)01090-2/fulltext

Summarizing patients’ problems from hospital progress notes using pre-trained sequence-to-sequence models

Published in Proceedings of the 29th International Conference on Computational …, 2022, 2022

Recommended citation:

Yanjun Gao, Dmitriy Dligach, Timothy A Miller, Dongfang Xu, Matthew MM Churpek, and Majid Afshar. 2022. Summarizing patients’ problems from hospital progress notes using pre-trained sequence-to-sequence models. In Proceedings of the 29th International Conference on Computational …, 2022. https://aclanthology.org/2022.coling-1.264.pdf

A scoping review of publicly available language tasks in clinical natural language processing

Published in Journal of the American Medical Informatics Association 29 (10), 1797-1806, 2022, 2022

Recommended citation:

Yanjun Gao, Dmitriy Dligach, Leslie Christensen, Samuel Tesch, Ryan Laffin, Dongfang Xu, Timothy Miller, Ozlem Uzuner, Matthew M Churpek, and Majid Afshar. 2022. A scoping review of publicly available language tasks in clinical natural language processing. In Journal of the American Medical Informatics Association 29 (10), 1797-1806, 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC9471718/pdf/ocac127.pdf

Classifying unstructured electronic consult messages to understand primary care physician specialty information needs

Published in Journal of the American Medical Informatics Association, 2022

Recommended citation:

Xiyu Ding, Michael Barnett, Ateev Mehrotra, Delphine S Tuot, Danielle S Bitterman, and Timothy A Miller. 2022. Classifying unstructured electronic consult messages to understand primary care physician specialty information needs. In Journal of the American Medical Informatics Association. https://pmc.ncbi.nlm.nih.gov/articles/PMC9382391/pdf/ocac092.pdf

US Food and Drug Administration approval of high-risk cardiovascular devices for use in children and adolescents, 1977-2021

Published in JAMA, 2022

Recommended citation:

Susmitha Wunnava, Timothy A Miller, Claire Narang, Meena Nathan, and Florence T Bourgeois. 2022. US Food and Drug Administration approval of high-risk cardiovascular devices for use in children and adolescents, 1977-2021. In JAMA. https://jamanetwork.com/journals/jama/articlepdf/2795037/jama_wunnava_2022_ld_220043_1659634162.5982.pdf

Ensemble-based fine-tuning strategy for temporal relation extraction from the clinical narrative

Published in Proceedings of the 4th Clinical Natural Language Processing Workshop, 103-108, 2022, 2022

Recommended citation:

Lijing Wang, Timothy A Miller, Steven Bethard, and Guergana K Savova. 2022. Ensemble-based fine-tuning strategy for temporal relation extraction from the clinical narrative. In Proceedings of the 4th Clinical Natural Language Processing Workshop, 103-108, 2022. https://aclanthology.org/2022.clinicalnlp-1.11.pdf

Hierarchical annotation for building a suite of clinical natural language processing tasks: Progress note understanding

Published in Proceedings of the Thirteenth Language Resources and Evaluation Conference …, 2022, 2022

Recommended citation:

Yanjun Gao, Dmitriy Dligach, Timothy A Miller, Samuel Tesch, Ryan Laffin, Matthew M Churpek, and Majid Afshar. 2022. Hierarchical annotation for building a suite of clinical natural language processing tasks: Progress note understanding. In Proceedings of the Thirteenth Language Resources and Evaluation Conference …, 2022. https://aclanthology.org/2022.lrec-1.587.pdf

A review of recent work in transfer learning and domain adaptation for natural language processing of electronic health records

Published in Yearbook of medical informatics 30 (01), 239-244, 2021, 2021

Recommended citation:

Egoitz Laparra, Aurelie Mascio, Sumithra Velupillai, and Timothy Miller. 2021. A review of recent work in transfer learning and domain adaptation for natural language processing of electronic health records. In Yearbook of medical informatics 30 (01), 239-244, 2021. https://www.thieme-connect.com/products/ejournals/html/10.1055/s-0041-1726522

Clinical natural language processing for radiation oncology: a review and practical primer

Published in International Journal of Radiation Oncology* Biology* Physics 110 (3), 641-655, 2021, 2021

Recommended citation:

MD Danielle S Bitterman, PhD Timothy A Miller, MD Raymond H Mak, and PhD Guergana K Savova. 2021. Clinical natural language processing for radiation oncology: a review and practical primer. In International Journal of Radiation Oncology* Biology* Physics 110 (3), 641-655, 2021. https://www.redjournal.org/article/S0360-3016(21)00118-8/pdf

EntityBERT: Entity-centric masking strategy for model pretraining for the clinical domain

Published in Proceedings of the 20th Workshop on Biomedical Language Processing, 191-201, 2021, 2021

Recommended citation:

Chen Lin, Timothy A Miller, Dmitriy Dligach, Steven Bethard, and Guergana K Savova. 2021. EntityBERT: Entity-centric masking strategy for model pretraining for the clinical domain. In Proceedings of the 20th Workshop on Biomedical Language Processing, 191-201, 2021. https://aclanthology.org/2021.bionlp-1.21.pdf

Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review

Published in Journal of biomedical informatics 115, 103671, 2021, 2021

Recommended citation:

Yuqi Si, Jingcheng Du, Zhao Li, Xiaoqian Jiang, Timothy Miller, Fei Wang, W Jim Zheng, and Kirk Roberts. 2021. Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review. In Journal of biomedical informatics 115, 103671, 2021. https://www.sciencedirect.com/science/article/pii/S1532046420302999

The SMART Cumulus Text-to-FHIR NLP Pipeline.

Published in AMIA, 2021, 2021

Recommended citation:

Timothy A Miller, Bin Mao, Dan Gottlieb, and Kenneth D Mandl. 2021. The SMART Cumulus Text-to-FHIR NLP Pipeline.. In AMIA, 2021.

Learning Hierarchical Transformer-based Representations of Clinical Notes

Published in American Medical Informatics Association Symposium, 2020, 2020

Recommended citation:

Xin Su, Timothy Miller, Majid Afshar, and Dmitriy Dligach. 2020. Learning Hierarchical Transformer-based Representations of Clinical Notes. In American Medical Informatics Association Symposium, 2020.

Incorporating risk factor embeddings in pre-trained transformers improves sentiment prediction in psychiatric discharge summaries

Published in Proceedings of the 3rd Clinical Natural Language Processing Workshop, 35-40, 2020, 2020

Recommended citation:

Xiyu Ding, Mei-Hua Hall, and Timothy A Miller. 2020. Incorporating risk factor embeddings in pre-trained transformers improves sentiment prediction in psychiatric discharge summaries. In Proceedings of the 3rd Clinical Natural Language Processing Workshop, 35-40, 2020. https://aclanthology.org/2020.clinicalnlp-1.4.pdf

Extracting relations between radiotherapy treatment details

Published in Proceedings of the 3rd clinical natural language processing workshop, 194-200, 2020, 2020

Recommended citation:

Danielle Bitterman, Timothy A Miller, David Harris, Chen Lin, Sean Finan, Jeremy Warner, Raymond Mak, and Guergana K Savova. 2020. Extracting relations between radiotherapy treatment details. In Proceedings of the 3rd clinical natural language processing workshop, 194-200, 2020. https://aclanthology.org/2020.clinicalnlp-1.21.pdf

Extracting radiotherapy treatment details using neural network-based natural language processing

Published in International Journal of Radiation Oncology, Biology, Physics, 2020

Recommended citation:

DS Bitterman, TA Miller, David Harris, Chen Lin, Sean Finan, Jeremy Warner, RH Mak, and GK Savova. 2020. Extracting radiotherapy treatment details using neural network-based natural language processing. In International Journal of Radiation Oncology, Biology, Physics. https://www.redjournal.org/article/S0360-3016(20)31638-2/pdf

Defining and learning refined temporal relations in the clinical narrative

Published in Proceedings of the 11th International Workshop on Health Text Mining and …, 2020, 2020

Recommended citation:

Kristin Wright-Bettner, Chen Lin, Timothy A Miller, Steven Bethard, Dmitriy Dligach, Martha Palmer, James H Martin, and Guergana K Savova. 2020. Defining and learning refined temporal relations in the clinical narrative. In Proceedings of the 11th International Workshop on Health Text Mining and …, 2020. https://aclanthology.org/2020.louhi-1.12.pdf

Methods for Extracting Information from Messages from Primary Care Providers to Specialists

Published in Proceedings of the First Workshop on Natural Language Processing for Medical …, 2020, 2020

Recommended citation:

Xiyu Ding, Michael Barnett, Ateev Mehrotra, and Timothy A Miller. 2020. Methods for Extracting Information from Messages from Primary Care Providers to Specialists. In Proceedings of the First Workshop on Natural Language Processing for Medical …, 2020. https://aclanthology.org/2020.nlpmc-1.1.pdf

A BERT-based one-pass multi-task model for clinical temporal relation extraction

Published in Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing …, 2020, 2020

Recommended citation:

Chen Lin, Timothy A Miller, Dmitriy Dligach, Farig Sadeque, Steven Bethard, and Guergana K Savova. 2020. A BERT-based one-pass multi-task model for clinical temporal relation extraction. In Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing …, 2020. https://aclanthology.org/2020.bionlp-1.7.pdf

Using Transformer-based Approaches for Measuring Semantic Similarity

Published in N2C2 2019 Shared Task Workshop at AMIA 2019, 2019, 2019

Recommended citation:

Xin Su, Timothy Miller, Farig Sadeque, Majid Afshar, and Dmitriy Dligach. 2019. Using Transformer-based Approaches for Measuring Semantic Similarity. In N2C2 2019 Shared Task Workshop at AMIA 2019, 2019.

Use of natural language processing to extract clinical cancer phenotypes from electronic medical records

Published in Cancer research 79 (21), 5463-5470, 2019, 2019

Recommended citation:

Guergana K Savova, Ioana Danciu, Folami Alamudun, Timothy Miller, Chen Lin, Danielle S Bitterman, Georgia Tourassi, and Jeremy L Warner. 2019. Use of natural language processing to extract clinical cancer phenotypes from electronic medical records. In Cancer research 79 (21), 5463-5470, 2019. https://aacrjournals.org/cancerres/article/79/21/5463/657598

Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse

Published in Journal of the American Medical Informatics Association, 2019

Recommended citation:

Dmitriy Dligach, Majid Afshar, and Timothy Miller. 2019. Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse. In Journal of the American Medical Informatics Association. https://pmc.ncbi.nlm.nih.gov/articles/PMC6798566/pdf/ocz072.pdf

Cross-document coreference: An approach to capturing coreference without context

Published in Proceedings of the Tenth International Workshop on Health Text Mining and …, 2019, 2019

Recommended citation:

Kristin Wright-Bettner, Martha Palmer, Guergana K Savova, Piet de Groen, and Timothy A Miller. 2019. Cross-document coreference: An approach to capturing coreference without context. In Proceedings of the Tenth International Workshop on Health Text Mining and …, 2019. https://aclanthology.org/D19-6201.pdf

Unsupervised learning of PCFGs with normalizing flow

Published in Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019, 2019

Recommended citation:

Lifeng Jin, Finale Doshi-Velez, Timothy A Miller, Lane Schwartz, and William Schuler. 2019. Unsupervised learning of PCFGs with normalizing flow. In Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019. https://aclanthology.org/P19-1234.pdf

A BERT-based universal model for both within-and cross-sentence clinical temporal relation extraction

Published in Proceedings of the 2nd clinical natural language processing workshop, 65-71, 2019, 2019

Recommended citation:

Chen Lin, Timothy A Miller, Dmitriy Dligach, Steven Bethard, and Guergana K Savova. 2019. A BERT-based universal model for both within-and cross-sentence clinical temporal relation extraction. In Proceedings of the 2nd clinical natural language processing workshop, 65-71, 2019. https://aclanthology.org/W19-1908.pdf

Extracting Drug Information with Apache cTAKES and ClearTK

Published in N2C2 2018 Shared Task Workshop at AMIA 2018, 2018, 2018

Recommended citation:

Timothy Miller and Dmitriy Dligach. 2018. Extracting Drug Information with Apache cTAKES and ClearTK. In N2C2 2018 Shared Task Workshop at AMIA 2018, 2018.

Self-training improves recurrent neural networks performance for temporal relation extraction

Published in Proceedings of the ninth international workshop on health text mining and …, 2018, 2018

Recommended citation:

Chen Lin, Timothy A Miller, Dmitriy Dligach, Hadi Amiri, Steven Bethard, and Guergana K Savova. 2018. Self-training improves recurrent neural networks performance for temporal relation extraction. In Proceedings of the ninth international workshop on health text mining and …, 2018. https://aclanthology.org/W18-5619.pdf

Expanding the diversity of texts and applications: findings from the section on clinical natural language processing of the international medical informatics association yearbook

Published in Yearbook of medical informatics, 2018

Recommended citation:

Aurélie Névéol and Pierre Zweigenbaum. 2018. Expanding the diversity of texts and applications: findings from the section on clinical natural language processing of the international medical informatics association yearbook. In Yearbook of medical informatics. https://www.thieme-connect.com/products/ejournals/html/10.1055/s-0038-1667080

Depth-bounding is effective: Improvements and evaluation of unsupervised PCFG induction

Published in Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018, 2018

Recommended citation:

Lifeng Jin, Finale Doshi-Velez, Timothy A Miller, William Schuler, and Lane Schwartz. 2018. Depth-bounding is effective: Improvements and evaluation of unsupervised PCFG induction. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018. https://aclanthology.org/D18-1292.pdf

DeepPhe: a natural language processing system for extracting cancer phenotypes from clinical records

Published in Cancer research, 2017

Recommended citation:

Guergana K Savova, Eugene Tseytlin, Sean Finan, Melissa Castine, Timothy Miller, Olga Medvedeva, David Harris, Harry Hochheiser, Chen Lin, Girish Chavan, and Rebecca S Jacobson. 2017. DeepPhe: a natural language processing system for extracting cancer phenotypes from clinical records. In Cancer research. https://aacrjournals.org/cancerres/article/77/21/e115/662609

Repeat before forgetting: Spaced repetition for efficient and effective training of neural networks

Published in Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017, 2017

Recommended citation:

Hadi Amiri, Timothy A Miller, and Guergana K Savova. 2017. Repeat before forgetting: Spaced repetition for efficient and effective training of neural networks. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017. https://aclanthology.org/D17-1255.pdf

Recurrent neural network architectures for event extraction from Italian medical reports

Published in Conference on Artificial Intelligence in Medicine in Europe, 198-202, 2017, 2017

Recommended citation:

Natalia Viani, Timothy A Miller, Dmitriy Dligach, Steven Bethard, Carlo Napolitano, Silvia G Priori, Riccardo Bellazzi, Lucia Sacchi, and Guergana K Savova. 2017. Recurrent neural network architectures for event extraction from Italian medical reports. In Conference on Artificial Intelligence in Medicine in Europe, 198-202, 2017.

Neural Models for Clinical Temporal Relation Extraction

Published in Midwest Speech and Language Days & Midwest Computational Linguistics …, 2017, 2017

Recommended citation:

Dmitriy Dligach, Timothy Miller, Chen Lin, Steven Bethard, and Guergana K Savova. 2017. Neural Models for Clinical Temporal Relation Extraction. In Midwest Speech and Language Days & Midwest Computational Linguistics …, 2017.

Neural temporal relation extraction

Published in Proceedings of the 15th Conference of the European Chapter of the …, 2017, 2017

Recommended citation:

Dmitriy Dligach, Timothy A Miller, Chen Lin, Steven Bethard, and Guergana K Savova. 2017. Neural temporal relation extraction. In Proceedings of the 15th Conference of the European Chapter of the …, 2017. https://aclanthology.org/E17-2118.pdf

Memory-bounded left-corner unsupervised grammar induction on child-directed input

Published in Proceedings of COLING 2016, the 26th International Conference on …, 2016, 2016

Recommended citation:

Cory Shain, William Bryce, Lifeng Jin, Victoria Krakovna, Finale Doshi-Velez, Timothy A Miller, William Schuler, and Lane Schwartz. 2016. Memory-bounded left-corner unsupervised grammar induction on child-directed input. In Proceedings of COLING 2016, the 26th International Conference on …, 2016. https://aclanthology.org/C16-1092.pdf

Cross-domain Coreference Feature Exploration

Published in AMIA Annual Symposium, 2016, 2016

Recommended citation:

Timothy Miller, Dmitriy Dligach, Chen Lin, Steven Bethard, and Guergana K Savova. 2016. Cross-domain Coreference Feature Exploration. In AMIA Annual Symposium, 2016.

Natural language processing–overview and history

Published in Pediatric Biomedical Informatics: Computer Applications in Pediatric …, 2016, 2016

Recommended citation:

Brian Connolly, Timothy Miller, Yizhao Ni, Kevin B Cohen, Guergana Savova, Judith W Dexheimer, and John Pestian. 2016. Natural language processing–overview and history. In Pediatric Biomedical Informatics: Computer Applications in Pediatric …, 2016.

Natural language processing: applications in pediatric research

Published in Pediatric Biomedical Informatics: Computer Applications in Pediatric …, 2016, 2016

Recommended citation:

Guergana Savova, John Pestian, Brian Connolly, Timothy Miller, Yizhao Ni, and Judith W Dexheimer. 2016. Natural language processing: applications in pediatric research. In Pediatric Biomedical Informatics: Computer Applications in Pediatric …, 2016.

Robust sentence segmentation for clinical text

Published in AMIA Annual Symposium, 2015, 2015

Recommended citation:

Timothy Miller, Sean Finan, Dmitriy Dligach, and Guergana K Savova. 2015. Robust sentence segmentation for clinical text. In AMIA Annual Symposium, 2015.

Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record

Published in Journal of the American Medical Informatics Association, 2015

Recommended citation:

Chen Lin, Elizabeth W Karlson, Dmitriy Dligach, Monica P Ramirez, Timothy A Miller, Huan Mo, Natalie S Braggs, Andrew Cagan, Vivian Gainer, Joshua C Denny, and Guergana K Savova. 2015. Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record. In Journal of the American Medical Informatics Association. https://academic.oup.com/jamia/article/22/e1/e151/701000

Descending-path convolution kernel for syntactic structures

Published in Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014, 2014

Recommended citation:

Chen Lin, Timothy A Miller, Alvin Kho, Steven Bethard, Dmitriy Dligach, Sameer Pradhan, and Guergana K Savova. 2014. Descending-path convolution kernel for syntactic structures. In Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014. https://aclanthology.org/P14-2014.pdf

Temporal annotation in the clinical domain

Published in Transactions of the association for computational linguistics, 2014

Recommended citation:

William F Styler IV, Steven Bethard, Sean Finan, Martha Palmer, Sameer Pradhan, Piet C De Groen, Brad Erickson, Timothy A Miller, Chen Lin, Guergana K Savova, and James Pustejovsky. 2014. Temporal annotation in the clinical domain. In Transactions of the association for computational linguistics. https://aclanthology.org/Q14-1012.pdf

Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium

Published in Journal of the American Medical Informatics Association, 2013

Recommended citation:

Jyotishman Pathak, Kent R Bailey, Calvin E Beebe, Steven Bethard, David S Carrell, Pei J Chen, Dmitriy Dligach, Cory M Endle, Lacey A Hart, Peter J Haug, Stanley M Huff, Vinod C Kaggal, Dingcheng Li, Hongfang Liu, Kyle Marchant, James Masanz, Timothy Miller, Thomas A Oniki, Martha Palmer, Kevin J Peterson, Susan Rea, Guergana K Savova, Craig R Stancl, Sunghwan Sohn, Harold R Solbrig, Dale B Suesse, Cui Tao, David P Taylor, Les Westberg, Stephen Wu, Ning Zhuo, and Christopher G Chute. 2013. Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium. In Journal of the American Medical Informatics Association. https://academic.oup.com/jamia/article/20/e2/e341/2909250

Discovering Time Expressions in Clinical Text

Published in American Medical Informatics Association Symposium, 2013, 2013

Recommended citation:

Timothy Miller, Dmitriy Dligach, Steven Bethard, Sameer S Pradhan, Chen Lin, and Guergana K Savova. 2013. Discovering Time Expressions in Clinical Text. In American Medical Informatics Association Symposium, 2013.

Active learning for phenotyping tasks

Published in Proceedings of the Workshop on NLP for Medicine and Biology associated with …, 2013, 2013

Recommended citation:

Dmitriy Dligach, Timothy A Miller, and Guergana K Savova. 2013. Active learning for phenotyping tasks. In Proceedings of the Workshop on NLP for Medicine and Biology associated with …, 2013. https://aclanthology.org/W13-5101.pdf

Automatic prediction of rheumatoid arthritis disease activity from the electronic medical records

Published in PloS one, 2013

Recommended citation:

Chen Lin, Elizabeth W Karlson, Helena Canhao, Timothy A Miller, Dmitriy Dligach, Pei Jun Chen, Raul Natanael Guzman Perez, Yuanyan Shen, Michael E Weinblatt, Nancy A Shadick, Robert M Plenge, and Guergana K Savova. 2013. Automatic prediction of rheumatoid arthritis disease activity from the electronic medical records. In PloS one. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0069932

Maximal information coefficient for feature selection for clinical document classification

Published in ICML workshop on machine learning for clinical data. Edingburgh, UK, 2012

Recommended citation:

Chen Lin, Timothy Miller, Dmitriy Dligach, R Plenge, E Karlson, and G Savova. 2012. Maximal information coefficient for feature selection for clinical document classification. In ICML workshop on machine learning for clinical data. Edingburgh, UK. https://people.cs.pitt.edu/~milos/icml_clinicaldata_2012/Papers/Poster_Chen_Guergana_ICML_Clinical_2012.pdf

Feature engineering and selection for rheumatoid arthritis disease activity classification using electronic medical records

Published in ICML Workshop on Machine Learning for Clinical Data Analysis, 2012

Recommended citation:

Chen Lin, Helena Canhao, Timothy Miller, Dmitriy Dligach, Robert M Plenge, Elizabeth W Karlson, and Guergana K Savova. 2012. Feature engineering and selection for rheumatoid arthritis disease activity classification using electronic medical records. In ICML Workshop on Machine Learning for Clinical Data Analysis. https://people.cs.pitt.edu/~milos/icml_clinicaldata_2012/Papers/Oral_Chen_Guergana_ICML_Clinical_2012.pdf

Generative models of disfluency

Published in University of Minnesota, 2010, 2010

Recommended citation:

Timothy A Miller. 2010. Generative models of disfluency. In University of Minnesota, 2010.

Incremental Semantic Models for Continuous Context-Sensitive Speech Recognition

Published in , 2008

Recommended citation:

Tim Miller, Lane Schwartz, and William Schuler. 2008. Incremental Semantic Models for Continuous Context-Sensitive Speech Recognition. https://www.researchgate.net/profile/Tim-Miller-2/publication/228806183_Incremental_Semantic_Models_for_Continuous_Context-Sensitive_Speech_Recognition/links/54749e550cf29afed60f8b56/Incremental-Semantic-Models-for-Continuous-Context-Sensitive-Speech-Recognition.pdf

Using Volunteers to Annotate Biomedical Corpora for Anaphora Resolution.

Published in AAAI Spring Symposium: Knowledge Collection from Volunteer Contributors, 117-, 2005, 2005

Recommended citation:

Shana Watters, Brian McInnes, David McKoskey, Tim Miller, Daniel Boley, Maria L Gini, William Schuler, A Polukeyeva, Jeanette K Gundel, Sergey V Pakhomov, and Guergana Savova. 2005. Using Volunteers to Annotate Biomedical Corpora for Anaphora Resolution.. In AAAI Spring Symposium: Knowledge Collection from Volunteer Contributors, 117-, 2005. https://cdn.aaai.org/Symposia/Spring/2005/SS-05-03/SS05-03-019.pdf