A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning. - Majid Afshar; Cara Joyce; Anthony Oakey; Perry Formanek; Philip Yang; Matthew M. Churpek; Richard S. Cooper; Ron Price; Susan J. Zelisko; Dmitriy Dligach (AMIA, 2018)

Towards a Universal Document-Level Clinical Text Encoder: Methods for Neural Network Pre-training with Applications to Substance Misuse. - Dmitriy Dligach; Majid Afshar; Timothy A. Miller (AMIA, 2019)

Untapped Potential of Clinical Text for Opioid Surveillance. - Amy L. Olex; Tamás Gál; Majid Afshar; Dmitriy Dligach; Niranjan S. Karnik; Travis Oakes; Brihat Sharma; Meng Xie; Bridget T. McInnes; Julian Solway; Abel N. Kho; William Cramer; et al. (AMIA, 2019)

Identification of Latent Subtypes of Patients with Opioid Misuse. - Brihat Sharma; Majid Afshar; Dmitriy Dligach; Robert Kanie; Elizabeth Salisbury-Afshar; Niranjan S. Karnik; Cara Joyce (AMIA, 2019)

Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies. - Majid Afshar; Dmitriy Dligach; Brihat Sharma; Xiaoyuan Cai; Jason Boyda; Steven Birch; Daniel Valdez; Suzan Zelisko; Cara Joyce; François Modave; Ron Price (J. Am. Medical Informatics Assoc., 2019)

Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation. - Majid Afshar; Andrew Phillips; Niranjan S. Karnik; Jeanne Mueller; Daniel To; Richard Gonzalez; Ron Price; Richard S. Cooper; Cara Joyce; Dmitriy Dligach (J. Am. Medical Informatics Assoc., 2019)

Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse. - Dmitriy Dligach; Majid Afshar; Timothy Miller 002 (J. Am. Medical Informatics Assoc., 2019)

Canadian Wetland Inventory using Google Earth Engine: The First Map and Preliminary Results. - Meisam Amani; Sahel Mahdavi; Majid Afshar; Brian Brisco; Weimin Huang 001; Sayyed Mohammad Javad Mirzadeh; Lori White; Sarah N. Banks; Joshua Montgomery; Christopher Hopkinson (Remote. Sens., 2019)

Learning Hierarchical Transformer-based Representations of Clinical Notes. - Xin Su 008; Timothy A. Miller; Majid Afshar; Dmitriy Dligach (AMIA, 2020)

High-dimensional feature selection for genomic datasets. - Majid Afshar; Hamid Usefi (Knowl. Based Syst., 2020)

Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients. - Brihat Sharma; Dmitriy Dligach; Kristin Swope; Elizabeth Salisbury-Afshar; Niranjan S. Karnik; Cara Joyce; Majid Afshar (BMC Medical Informatics Decis. Mak., 2020)

Bias Assessment and Correction in Machine Learning Algorithms: A Use-Case in a Natural Language Processing Algorithm to Identify Hospitalized Patients with Unhealthy Alcohol Use. - Marissa Borgese; Cara Joyce; Emily E. Anderson; Matthew M. Churpek; Majid Afshar (AMIA, 2021)

Sepsis Prediction Using Semi-Supervised and Transfer Learning. - John R. Caskey; Fereshteh S. Bashiri; Anoop M. Mayampurath; Nicole Dussault; Jay Dumanian; Sivasubramanium V. Bhavani; Kyle A. Carey; Emily R. Gilbert; Christopher J. Winslow; Nirav S. Shah; Dana P. Edelson; Majid Afshar; et al. (AMIA, 2021)

A multi-label classifier to screen different types of substance misuse in hospitalized patients. - Brihat Sharma; Dmitriy Dligach; Hale Thomson; Matthew M. Churpek; Niranjan S. Karnik; Majid Afshar (AMIA, 2021)

The Addition of United States Census-Tract Data Does Not Improve the Prediction of Substance Misuse. - Daniel To; Cara Joyce; Sujay Kulshrestha; Brihat Sharma; Dmitriy Dligach; Matthew M. Churpek; Majid Afshar (AMIA, 2021)

Incorporating Behavior in Attribute Based Access Control Model Using Machine Learning. - Majid Afshar; Saeed Samet; Hamid Usefi (SysCon, 2021)

Classifying Long Clinical Documents with Pre-trained Transformers. - Xin Su 008; Timothy Miller 002; Xiyu Ding; Majid Afshar; Dmitriy Dligach (CoRR, 2021)

Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups. - Hale M. Thompson; Brihat Sharma; Sameer Bhalla; Randy Boley; Connor McCluskey; Dmitriy Dligach; Matthew M. Churpek; Niranjan S. Karnik; Majid Afshar (J. Am. Medical Informatics Assoc., 2021)

Pre-training phenotyping classifiers. - Dmitriy Dligach; Majid Afshar; Timothy Miller 002 (J. Biomed. Informatics, 2021)

Explaining Alerts from a Pediatric Deterioration Prediction Model Using Clinical Text. - Anoop M. Mayampurath; Kyle A. Carey; Priti Jani; Majid Afshar; Matthew M. Churpek; Dmitriy Dligach (AMIA, 2022)

Summarizing Patients' Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models. - Yanjun Gao; Dmitriy Dligach; Timothy Miller 002; Dongfang Xu; Matthew M. Churpek; Majid Afshar (COLING, 2022)

Hierarchical Annotation for Building A Suite of Clinical Natural Language Processing Tasks: Progress Note Understanding. - Yanjun Gao; Dmitriy Dligach; Timothy Miller 002; Samuel Tesch; Ryan Laffin; Matthew M. Churpek; Majid Afshar (LREC, 2022)

Optimizing feature selection methods by removing irrelevant features using sparse least squares. - Majid Afshar; Hamid Usefi (Expert Syst. Appl., 2022)

Governance of Clinical AI applications to facilitate safe and equitable deployment in a large health system: Key elements and early successes. - Frank Liao; Sabrina Adelaine; Majid Afshar; Brian W. Patterson (Frontiers Digit. Health, 2022)

Image and structured data analysis for prognostication of health outcomes in patients presenting to the ED during the COVID-19 pandemic. - Liam Butler; Ibrahim Karabayir; Mohammad Samie Tootooni; Majid Afshar; Ari Goldberg; Oguz Akbilgic (Int. J. Medical Informatics, 2022)

Identifying infected patients using semi-supervised and transfer learning. - Fereshteh S. Bashiri; John R. Caskey; Anoop M. Mayampurath; Nicole Dussault; Jay Dumanian; Sivasubramanium V. Bhavani; Kyle A. Carey; Emily R. Gilbert; Christopher J. Winslow; Nirav S. Shah; Dana P. Edelson; Majid Afshar; et al. (J. Am. Medical Informatics Assoc., 2022)

A scoping review of publicly available language tasks in clinical natural language processing. - Yanjun Gao; Dmitriy Dligach; Leslie Christensen; Samuel Tesch; Ryan Laffin; Dongfang Xu; Timothy Miller 002; Özlem Uzuner; Matthew M. Churpek; Majid Afshar (J. Am. Medical Informatics Assoc., 2022)

Multi-Task Training with In-Domain Language Models for Diagnostic Reasoning. - Brihat Sharma; Yanjun Gao; Timothy Miller 002; Matthew M. Churpek; Majid Afshar; Dmitriy Dligach (ClinicalNLP@ACL, 2023)

Improving the Transferability of Clinical Note Section Classification Models with BERT and Large Language Model Ensembles. - Weipeng Zhou; Majid Afshar; Dmitriy Dligach; Yanjun Gao; Timothy A. Miller (ClinicalNLP@ACL, 2023)

Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress Notes. - Yanjun Gao; Dmitriy Dligach; Timothy Miller 002; Majid Afshar (BioNLP@ACL, 2023)

Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress Notes. - Yanjun Gao; Dmitriy Dligach; Timothy Miller 002; Matthew M. Churpek; Majid Afshar (CoRR, 2023)

Leveraging A Medical Knowledge Graph into Large Language Models for Diagnosis Prediction. - Yanjun Gao; Ruizhe Li 001; John R. Caskey; Dmitriy Dligach; Timothy Miller 002; Matthew M. Churpek; Majid Afshar (CoRR, 2023)

Considerations for health care institutions training large language models on electronic health records. - Weipeng Zhou; Danielle S. Bitterman; Majid Afshar; Timothy A. Miller (CoRR, 2023)

The impact of using an AI chatbot to respond to patient messages. - Shan Chen 004; Marco Guevara; Shalini Moningi; Frank Hoebers; Hesham Elhalawani; Benjamin H. Kann; Fallon E. Chipidza; Jonathan Leeman; Hugo J. W. L. Aerts; Timothy A. Miller; Guergana K. Savova; Raymond H. Mak; et al. (CoRR, 2023)

DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing. - Yanjun Gao; Dmitriy Dligach; Timothy Miller 002; John R. Caskey; Brihat Sharma; Matthew M. Churpek; Majid Afshar (J. Biomed. Informatics, 2023)

Progress Note Understanding - Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 shared task. - Yanjun Gao; Dmitriy Dligach; Timothy Miller 002; Matthew M. Churpek; Özlem Uzuner; Majid Afshar (J. Biomed. Informatics, 2023)

Improving model transferability for clinical note section classification models using continued pretraining. - Weipeng Zhou; Meliha Yetisgen; Majid Afshar; Yanjun Gao; Guergana Savova; Timothy A. Miller (J. Am. Medical Informatics Assoc., 2023)

When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications? - Yanjun Gao; Skatje Myers; Shan Chen 004; Dmitriy Dligach; Timothy A. Miller; Danielle S. Bitterman; Matthew M. Churpek; Majid Afshar (EMNLP (Findings), 2024)

Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data. - Shan Chen 004; Jack Gallifant; Marco Guevara; Yanjun Gao; Majid Afshar; Timothy Miller 002; Dmitriy Dligach; Danielle S. Bitterman (CoRR, 2024)

Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review. - Emma Croxford; Yanjun Gao; Nicholas Pellegrino; Karen K. Wong; Graham Wills; Elliot First; Frank J. Liao; Cherodeep Goswami; Brian W. Patterson; Majid Afshar (CoRR, 2024)

Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability. - Yanjun Gao; Skatje Myers; Shan Chen 004; Dmitriy Dligach; Timothy A. Miller; Danielle S. Bitterman; Guanhua Chen; Anoop M. Mayampurath; Matthew M. Churpek; Majid Afshar (CoRR, 2024)

Development and external validation of deep learning clinical prediction models using variable-length time series data. - Fereshteh S. Bashiri; Kyle A. Carey; Jennie Martin; Jay L. Koyner; Dana P. Edelson; Emily R. Gilbert; Anoop M. Mayampurath; Majid Afshar; Matthew M. Churpek (J. Am. Medical Informatics Assoc., 2024)

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models. - Jifan Gao; Guanhua Chen; Ann P. O'Rourke; John R. Caskey; Kyle A. Carey; Madeline Oguss; Anne Stey; Dmitriy Dligach; Timothy Miller 002; Anoop M. Mayampurath; Matthew M. Churpek; Majid Afshar (J. Am. Medical Informatics Assoc., 2024)

On the role of the UMLS in supporting diagnosis generation proposed by Large Language Models. - Majid Afshar; Yanjun Gao; Deepak Gupta; Emma Croxford; Dina Demner-Fushman (J. Biomed. Informatics, 2024)

Exploring RAG Solutions to Reduce Hallucinations in LLMs. - Samar AboulEla; Paria Zabihitari; Nourhan Ibrahim; Majid Afshar; Rasha F. Kashef (SysCon, 2025)

Development and validation of the provider documentation summarization quality instrument for large language models. - Emma Croxford; Yanjun Gao; Nicholas Pellegrino; Karen K. Wong; Graham Wills; Elliot First; Miranda Schnier; Kyle Burton; Cris G. Ebby; Jillian Gorskic; Matthew Kalscheur; Samy Khalil; et al. (J. Am. Medical Informatics Assoc., 2025)

Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies. - Skatje Myers; Timothy A. Miller; Yanjun Gao; Matthew M. Churpek; Anoop M. Mayampurath; Dmitriy Dligach; Majid Afshar (J. Am. Medical Informatics Assoc., 2025)

LCD benchmark: long clinical document benchmark on mortality prediction for language models. - Wonjin Yoon; Shan Chen 004; Yanjun Gao; Zhanzhan Zhao; Dmitriy Dligach; Danielle S. Bitterman; Majid Afshar; Timothy A. Miller (J. Am. Medical Informatics Assoc., 2025)

An Information-Theoretic Perspective on Multi-LLM Uncertainty Estimation. - Maya Kruse; Majid Afshar; Saksham Khatwani; Anoop M. Mayampurath; Guanhua Chen; Yanjun Gao (CoRR, 2025)