Text Categorization Models for Retrieval of High Quality Articles in Internal Medicine. - Yindalon Aphinyanaphongs; Constantin F. Aliferis (AMIA, 2003)

Learning Boolean Queries for Article Quality Filtering. - Yin Aphinyanaphongs; Constantin F. Aliferis (MedInfo, 2004)

Research Paper: Text Categorization Models for High-Quality Article Retrieval in Internal Medicine. - Yindalon Aphinyanaphongs; Ioannis Tsamardinos; Alexander R. Statnikov; Douglas P. Hardin; Constantin F. Aliferis (J. Am. Medical Informatics Assoc., 2005)

Prospective Validation of Text Categorization Filters for Identifying High-Quality, Content-Specific Articles in MEDLINE. - Yindalon Aphinyanaphongs; Constantin F. Aliferis (AMIA, 2006)

Research Paper: A Comparison of Citation Metrics to Machine Learning Filters for the Identification of High Quality MEDLINE Documents. - Yindalon Aphinyanaphongs; Alexander R. Statnikov; Constantin F. Aliferis (J. Am. Medical Informatics Assoc., 2006)

Research Paper: Using Citation Data to Improve Retrieval from MEDLINE. - Elmer V. Bernstam; Jorge R. Herskovic; Yindalon Aphinyanaphongs; Constantin F. Aliferis; Madurai G. Sriram; William R. Hersh (J. Am. Medical Informatics Assoc., 2006)

Text Categorization Models for Identifying Unproven Cancer Treatments on the Web. - Yindalon Aphinyanaphongs; Constantin F. Aliferis (MedInfo, 2007)

A Comparison of Impact Factor, Clinical Query Filters, and Pattern Recognition Query Filters in Terms of Sensitivity to Topic. - Lawrence D. Fu; Lily Wang 001; Yindalon Aphinyanagphongs; Constantin F. Aliferis (MedInfo, 2007)

A comparison of evaluation metrics for biomedical journals, articles, and websites in terms of sensitivity to topic. - Lawrence D. Fu; Yindalon Aphinyanaphongs; Lily Wang 001; Constantin F. Aliferis (J. Biomed. Informatics, 2011)

Using Knowledge from APIs to Disambiguate Affiliation Names in MEDLINE. - Karen Hanson; Yindalon Aphinyanaphongs; Lawrence D. Fu (AMIA, 2012)

Feasibility of Machine Learning Based Automatic Classification of Medical School Curricula. - Bisakha Ray; Lawrence D. Fu; William Holloway; Yindalon Aphinyanaphongs (AMIA, 2013)

Identifying Unproven Cancer Treatments on the Health Web: Addressing Accuracy, Generalizability and Scalability. - Yindalon Aphinyanaphongs; Lawrence D. Fu; Constantin F. Aliferis (MedInfo, 2013)

Computer models for identifying instrumental citations in the biomedical literature. - Lawrence D. Fu; Yindalon Aphinyanaphongs; Constantin F. Aliferis (Scientometrics, 2013)

Text classification for automatic detection of alcohol use-related tweets: A feasibility study. - Yin Aphinyanaphongs; Bisakha Ray; Alexander R. Statnikov; Paul Krebs (IRI, 2014)

A comprehensive empirical comparison of modern supervised classification and feature selection methods for text categorization. - Yindalon Aphinyanaphongs; Lawrence D. Fu; Zhiguo Li; Eric R. Peskin; Efstratios Efstathiadis; Constantin F. Aliferis; Alexander R. Statnikov (J. Assoc. Inf. Sci. Technol., 2014)

Building and evaluating predictive models for postoperative ileus prior to colorectal surgery. - Xuya Wang; Raul Caso Caso; Yindalon Aphinyanaphongs (AMIA, 2015)

Text Classification-Based Automatic Recruitment of Patients for Clinical Trials: A Silver Standards-Based Case Study. - Bisakha Ray; Yindalon Aphinyanaphongs; Sean Heffron (ICHI, 2015)

Simplifying PheWAS Analysis: An R Package and Teaching Module. - Emily Kawaler; Yindalon Aphinyanaphongs (AMIA, 2016)

Reusable Filtering Functions for Application in ICU data: a case study. - Vincent J. Major; Monique S. Tanna; Simon Jones 002; Yindalon Aphinyanaphongs (AMIA, 2016)

Text Classification for Automatic Detection of E-Cigarette Use and Use for Smoking Cessation from Twitter: A Feasibility Pilot. - Yin Aphinyanaphongs; Armine Lulejian; Duncan Penfold-Brown; Richard Bonneau; Paul Krebs (PSB, 2016)

The Good, The Bad, and The Ugly of Deploying and Adopting Machine Learning Based Models in Clinical Practice. - Yin Aphinyanaphongs; David Holmes; Berkman Sahiner; Parsa Mirhaji; Michael Draugelis (AMIA, 2017)

Optimizing Parameters of word2vec for a Text Classification Task. - Vincent J. Major; Alisa Surkis; Yindalon Aphinyanaphongs (AMIA, 2017)

Neural Network Word Embeddings for Text Classification of MeSH terms. - Walter Wang; Yindalon Aphinyanaphongs (AMIA, 2017)

A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations. - Josua Krause; Aritra Dasgupta 001; Jordan Swartz; Yindalon Aphinyanaphongs; Enrico Bertini (VAST, 2017)

A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations. - Josua Krause; Aritra Dasgupta 004; Jordan Swartz; Yindalon Aphinyanaphongs; Enrico Bertini (CoRR, 2017)

Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research. - Vincent J. Major; Alisa Surkis; Yindalon Aphinyanaphongs (AMIA, 2018)

Translating, Implementing, Deploying, and Evaluating Clinical Interventions Using Machine Learning Based Predictive Models: Illustrative Case Studies. - Yindalon Aphinyanaphongs; Jonathan K. Wilt; Corey J. Chivers; Mark P. Sendak (AMIA, 2019)

The Process of Developing, Validating and Operationalizing a Personalized Machine Learning Algorithm for Clinical Decision Support: A Case Study. - Sara Kuppin Chokshi; Ji Chen; Roshini Hegde; Eduardo Iturrate; Yindalon Aphinyanaphongs; Javier Gonzalez; Devin M. Mann (AMIA, 2019)

SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing. - Isabel Metzger; Emir Y. Haskovic; Allison Black; Whitley M. Yi; Rajat S. Chandra; Mark T. Rutledge; William McMahon; Yindalon Aphinyanaphongs (SMM4H@COLING, 2020)

Assessment of Amazon Comprehend Medical: Medication Information Extraction. - Benedict Guzman; Isabel Metzger; Yindalon Aphinyanaphongs; Himanshu Grover (CoRR, 2020)

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. - Farah E. Shamout; Yiqiu Shen; Nan Wu 008; Aakash Kaku; Jungkyu Park 001; Taro Makino; Stanislaw Jastrzebski; Duo Wang; Ben Zhang; Siddhant Dogra; Meng Cao; Narges Razavian; et al. (CoRR, 2020)

The Transformation of Patient-Clinician Relationships With AI-Based Medical Advice: A "Bring Your Own Algorithm" Era in Healthcare. - Oded Nov; Yindalon Aphinyanaphongs; Yvonne W. Lui; Devin M. Mann; Maurizio Porfiri; Mark O. Riedl; John-Ross Rizzo; Batia Mishan Wiesenfeld (CoRR, 2020)

Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites. - Vincent J. Major; Yindalon Aphinyanaphongs (BMC Medical Informatics Decis. Mak., 2020)

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients. - Narges Razavian; Vincent J. Major; Mukund Sudarshan; Jesse Burk-Rafel; Peter Stella; Hardev Randhawa; Seda Bilaloglu; Ji Chen; Vuthy Nguy; Walter Wang; Hao Zhang; Ilan Reinstein; et al. (npj Digit. Medicine, 2020)

Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations. - Neil Jethani; Mukund Sudarshan; Yindalon Aphinyanaphongs; Rajesh Ranganath (AISTATS, 2021)

Data-Driven Patterns in Protective Effects of Ibuprofen and Ketorolac on Hospitalized Covid-19 Patients. - Rich Caruana; Benjamin J. Lengerich; Yindalon Aphinyanaphongs (AMIA, 2021)

Prediction of Resuscitation for Pediatric Sepsis from Data Available at Triage. - Peter A. Stella; Elizabeth Haines; Yindalon Aphinyanaphongs (AMIA, 2021)

Expanding the Reach of Structured EHR Data with Clinical Notes Improving End-of-Life Prediction. - Seda Bilaloglu; Vincent J. Major; Himanshu Grover; Isabel Metzger; Yindalon Aphinyanaphongs (FLAIRS, 2021)

The transformation of patient-clinician relationships with AI-based medical advice. - Oded Nov; Yindalon Aphinyanaphongs; Yvonne W. Lui; Devin M. Mann; Maurizio Porfiri; Mark O. Riedl; John-Ross Rizzo; Batia Mishan Wiesenfeld (Commun. ACM, 2021)

COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. - Anuroop Sriram; Matthew J. Muckley; Koustuv Sinha; Farah Shamout; Joelle Pineau; Krzysztof J. Geras; Lea Azour; Yindalon Aphinyanaphongs; Nafissa Yakubova; William Moore (CoRR, 2021)

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. - Farah E. Shamout; Yiqiu Shen; Nan Wu 008; Aakash Kaku; Jungkyu Park 001; Taro Makino; Stanislaw Jastrzebski; Jan Witowski; Duo Wang; Ben Zhang; Siddhant Dogra; Meng Cao; et al. (npj Digit. Medicine, 2021)

Quantitative and Qualitative Evaluation of Provider Use of a Novel Machine Learning Model for Favorable Outcome Prediction. - Elisabeth Yang; Yin Aphinyanaphongs; Paawan Punjabi; Jonathan S. Austrian; Batia Mishan Wiesenfeld (AMIA, 2022)

New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography. - Neil Jethani; Aahlad Manas Puli; Hao Zhang; Leonid Garber; Lior Jankelson; Yindalon Aphinyanaphongs; Rajesh Ranganath (CoRR, 2022)

Estimating Discontinuous Time-Varying Risk Factors and Treatment Benefits for COVID-19 with Interpretable ML. - Benjamin J. Lengerich; Mark E. Nunnally; Yin Aphinyanaphongs; Rich Caruana (CoRR, 2022)

Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study. - Benjamin J. Lengerich; Mark E. Nunnally; Yin Aphinyanaphongs; Caleb Ellington; Rich Caruana (J. Biomed. Informatics, 2022)

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial. - Vincent J. Major; Simon Andrew Jones; Narges Razavian; Ashley Bagheri; Felicia Mendoza; Jay Stadelman; Leora I. Horwitz; Jonathan S. Austrian; Yindalon Aphinyanaphongs (Appl. Clin. Inform., 2022)

AI model transferability in healthcare: a sociotechnical perspective. - Batia Mishan Wiesenfeld; Yin Aphinyanaphongs; Oded Nov (Nat. Mac. Intell., 2022)

Ten Years of Health Informatics Education for Physicians. - Vincent J. Major; Claudia S. Plottel; Yindalon Aphinyanaphongs (ICHI, 2023)

Enabling AI-Augmented Clinical Workflows by Accessing Patient Data in Real-Time with FHIR. - Vincent J. Major; Walter Wang; Yindalon Aphinyanaphongs (ICHI, 2023)

A dynamic risk score for early prediction of cardiogenic shock using machine learning. - Yuxuan Hu; Albert Lui; Mark Goldstein; Mukund Sudarshan; Andrea Tinsay; Cindy Tsui; Samuel Maidman; John Medamana; Neil Jethani; Aahlad Manas Puli; Vuthy Nguy; Yindalon Aphinyanaphongs; et al. (CoRR, 2023)

Diagnosis Uncertain Models For Medical Risk Prediction. - Alexander Peysakhovich; Rich Caruana; Yin Aphinyanaphongs (CoRR, 2023)

LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs. - Benjamin J. Lengerich; Sebastian Bordt; Harsha Nori; Mark E. Nunnally; Yin Aphinyanaphongs; Manolis Kellis; Rich Caruana (CoRR, 2023)

Health system-scale language models are all-purpose prediction engines. - Lavender Yao Jiang; Xujin Chris Liu; Nima Pour Nejatian; Mustafa Nasir-Moin; Duo Wang; Anas Z. Abidin; Kevin Eaton; Howard Antony Riina; Ilya Laufer; Paawan Punjabi; Madeline Miceli; Nora C. Kim; et al. (Nat., 2023)

NYULangone at Chemotimelines 2024: Utilizing Open-Weights Large Language Models for Chemotherapy Event Extraction. - Jeff Zhang 004; Yin Aphinyanaphongs; Anthony Cardillo (ClinicalNLP@NAACL, 2024)

Seeing Beyond Borders: Evaluating LLMs in Multilingual Ophthalmological Question Answering. - David S. Restrepo; Luis Filipe Nakayama; Robyn Gayle Dychiao; Chenwei Wu 006; Liam G. McCoy; Jose Carlo Artiaga; Marisa Cobanaj; João Matos; Jack Gallifant; Danielle S. Bitterman; Vincenz Ferrer; Yindalon Aphinyanaphongs; et al. (ICHI, 2024)

Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model. - Salman Rahman; Lavender Yao Jiang; Saadia Gabriel; Yindalon Aphinyanaphongs; Eric Karl Oermann; Rumi Chunara (CoRR, 2024)

Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings. - Kar-mun C. Woo; Gregory W. Simon; Olumide Akindutire; Yindalon Aphinyanaphongs; Jonathan S. Austrian; Jung G. Kim; Nicholas Genes; Jacob A Goldenring; Vincent J. Major; Chloé S. Pariente; Edwin G. Pineda; Stella K. Kang (J. Am. Medical Informatics Assoc., 2024)

Health system-wide access to generative artificial intelligence: the New York University Langone Health experience. - Kiran Malhotra; Batia Mishan Wiesenfeld; Vincent J. Major; Himanshu Grover; Yindalon Aphinyanaphongs; Paul A. Testa; Jonathan S. Austrian (J. Am. Medical Informatics Assoc., 2025)

Repurposing the scientific literature with vision-language models. - Anton Alyakin; Jaden Stryker; Daniel Alexander Alber; Karl L. Sangwon; Brandon Duderstadt; Akshay Save; David Kurland; Spencer Frome; Shrutika Singh; Jeff Zhang 004; Eunice Yang; Ki Yun Park; et al. (CoRR, 2025)