Yindalon Aphinyanaphongs

52 papers A 1Misc 15Journal 28Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Large Language Models Predict Functional Outcomes after Acute Ischemic Stroke. CoRR Anjali K. Kapoor, Anton Alyakin, Jin Vivian Lee, Eunice Yang, Annelene M. Schulze, Krithik Vishwanath, Jinseok Lee, Yindalon Aphinyanaphongs, Howard Riina, Jennifer A. Frontera, Eric Karl Oermann
2025	J	`jnl`	Generalist Foundation Models Are Not Clinical Enough for Hospital Operations. CoRR Lavender Y. Jiang, Angelica Chen, Xu Han, Xujin Chris Liu, Radhika Dua, Kevin Eaton, Frederick Wolff, Robert Steele, Jeff Zhang, Anton Alyakin, Qingkai Pan, Yanbing Chen, Karl L. Sangwon, Daniel Alexander Alber, Jaden Stryker, Jin Vivian Lee, Yindalon Aphinyanaphongs, Kyunghyun Cho, Eric Karl Oermann
2025	J	`jnl`	Generalist Large Language Models Outperform Clinical Tools on Medical Benchmarks. CoRR Krithik Vishwanath, Mrigayu Ghosh, Anton Alyakin, Daniel Alexander Alber, Yindalon Aphinyanaphongs, Eric Karl Oermann
2025	J	`jnl`	Health system-wide access to generative artificial intelligence: the New York University Langone Health experience. J. Am. Medical Informatics Assoc. Kiran Malhotra, Batia Mishan Wiesenfeld, Vincent J. Major, Himanshu Grover, Yindalon Aphinyanaphongs, Paul A. Testa, Jonathan S. Austrian
2025	J	`jnl`	Repurposing the scientific literature with vision-language models. CoRR Anton Alyakin, Jaden Stryker, Daniel Alexander Alber, Karl L. Sangwon, Brandon Duderstadt, Akshay Save, David Kurland, Spencer Frome, Shrutika Singh, Jeff Zhang, Eunice Yang, Ki Yun Park, Cordelia Orillac, Aly A. Valliani, Sean Neifert, Albert Liu, Aneek Patel, Christopher Livia, Darryl Lau, Ilya Laufer, Peter A. Rozman, Eveline Teresa Hidalgo, Howard Riina, Rui Feng, Todd C. Hollon, Yindalon Aphinyanaphongs, John G. Golfinos, Laura Snyder, Eric Leuthardt, Douglas Kondziolka, Eric Karl Oermann
2024	J	`jnl`	Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings. J. Am. Medical Informatics Assoc. 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
2024	J	`jnl`	Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model. CoRR Salman Rahman, Lavender Yao Jiang, Saadia Gabriel, Yindalon Aphinyanaphongs, Eric Karl Oermann, Rumi Chunara
2024	—	`conf`	Seeing Beyond Borders: Evaluating LLMs in Multilingual Ophthalmological Question Answering. ICHI David S. Restrepo, Luis Filipe Nakayama, Robyn Gayle Dychiao, Chenwei Wu, Liam G. McCoy, Jose Carlo Artiaga, Marisa Cobanaj, João Matos, Jack Gallifant, Danielle S. Bitterman, Vincenz Ferrer, Yindalon Aphinyanaphongs, Leo Anthony Celi
2023	J	`jnl`	A dynamic risk score for early prediction of cardiogenic shock using machine learning. CoRR 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, Nicholas Kiefer, Nathaniel Smilowitz, James Horowitz, Tania Ahuja, Glenn I. Fishman, Judith Hochman, Stuart Katz, Samuel Bernard, Rajesh Ranganath
2023	—	`conf`	Enabling AI-Augmented Clinical Workflows by Accessing Patient Data in Real-Time with FHIR. ICHI Vincent J. Major, Walter Wang, Yindalon Aphinyanaphongs
2023	J	`jnl`	Health system-scale language models are all-purpose prediction engines. Nat. 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, Cordelia Orillac, Zane Schnurman, Christopher Livia, Hannah Weiss, David Kurland, Sean Neifert, Yosef Dastagirzada, Douglas Kondziolka, Alexander T. M. Cheung, Grace Yang, Ming Cao, Mona Flores, Anthony B. Costa, Yindalon Aphinyanaphongs, Kyunghyun Cho, Eric Karl Oermann
2023	—	`conf`	Ten Years of Health Informatics Education for Physicians. ICHI Vincent J. Major, Claudia S. Plottel, Yindalon Aphinyanaphongs
2022	J	`jnl`	Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial. Appl. Clin. Inform. Vincent J. Major, Simon Andrew Jones, Narges Razavian, Ashley Bagheri, Felicia Mendoza, Jay Stadelman, Leora I. Horwitz, Jonathan S. Austrian, Yindalon Aphinyanaphongs
2022	J	`jnl`	New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography. CoRR Neil Jethani, Aahlad Manas Puli, Hao Zhang, Leonid Garber, Lior Jankelson, Yindalon Aphinyanaphongs, Rajesh Ranganath
2021	J	`jnl`	An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. npj Digit. Medicine Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras
2021	J	`jnl`	COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. CoRR Anuroop Sriram, Matthew J. Muckley, Koustuv Sinha, Farah Shamout, Joelle Pineau, Krzysztof J. Geras, Lea Azour, Yindalon Aphinyanaphongs, Nafissa Yakubova, William Moore
2021	Misc	`conf`	Data-Driven Patterns in Protective Effects of Ibuprofen and Ketorolac on Hospitalized Covid-19 Patients. AMIA Rich Caruana, Benjamin J. Lengerich, Yindalon Aphinyanaphongs
2021	Misc	`conf`	Expanding the Reach of Structured EHR Data with Clinical Notes Improving End-of-Life Prediction. FLAIRS Seda Bilaloglu, Vincent J. Major, Himanshu Grover, Isabel Metzger, Yindalon Aphinyanaphongs
2021	A	`conf`	Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations. AISTATS Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath
2021	J	`jnl`	Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations. CoRR Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath
2021	Misc	`conf`	Prediction of Resuscitation for Pediatric Sepsis from Data Available at Triage. AMIA Peter A. Stella, Elizabeth Haines, Yindalon Aphinyanaphongs
2021	J	`jnl`	The transformation of patient-clinician relationships with AI-based medical advice. Commun. ACM Oded Nov, Yindalon Aphinyanaphongs, Yvonne W. Lui, Devin M. Mann, Maurizio Porfiri, Mark O. Riedl, John-Ross Rizzo, Batia Mishan Wiesenfeld
2020	J	`jnl`	A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients. npj Digit. Medicine 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, David Kudlowitz, Cameron Zenger, Meng Cao, Ruina Zhang, Siddhant Dogra, Keerthi B. Harish, Brian Bosworth, Fritz Francois, Leora I. Horwitz, Rajesh Ranganath, Jonathan S. Austrian, Yindalon Aphinyanaphongs
2020	J	`jnl`	An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. CoRR Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras
2020	J	`jnl`	Assessment of Amazon Comprehend Medical: Medication Information Extraction. CoRR Benedict Guzman, Isabel Metzger, Yindalon Aphinyanaphongs, Himanshu Grover
2020	J	`jnl`	Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites. BMC Medical Informatics Decis. Mak. Vincent J. Major, Yindalon Aphinyanaphongs
2020	—	`conf`	SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing. SMM4H@COLING Isabel Metzger, Emir Y. Haskovic, Allison Black, Whitley M. Yi, Rajat S. Chandra, Mark T. Rutledge, William McMahon, Yindalon Aphinyanaphongs
2020	J	`jnl`	The Transformation of Patient-Clinician Relationships With AI-Based Medical Advice: A "Bring Your Own Algorithm" Era in Healthcare. CoRR Oded Nov, Yindalon Aphinyanaphongs, Yvonne W. Lui, Devin M. Mann, Maurizio Porfiri, Mark O. Riedl, John-Ross Rizzo, Batia Mishan Wiesenfeld
2019	Misc	`conf`	The Process of Developing, Validating and Operationalizing a Personalized Machine Learning Algorithm for Clinical Decision Support: A Case Study. AMIA Sara Kuppin Chokshi, Ji Chen, Roshini Hegde, Eduardo Iturrate, Yindalon Aphinyanaphongs, Javier Gonzalez, Devin M. Mann
2019	Misc	`conf`	Translating, Implementing, Deploying, and Evaluating Clinical Interventions Using Machine Learning Based Predictive Models: Illustrative Case Studies. AMIA Yindalon Aphinyanaphongs, Jonathan K. Wilt, Corey J. Chivers, Mark P. Sendak
2018	Misc	`conf`	Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research. AMIA Vincent J. Major, Alisa Surkis, Yindalon Aphinyanaphongs
2017	—	`conf`	A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations. VAST Josua Krause, Aritra Dasgupta, Jordan Swartz, Yindalon Aphinyanaphongs, Enrico Bertini
2017	J	`jnl`	A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations. CoRR Josua Krause, Aritra Dasgupta, Jordan Swartz, Yindalon Aphinyanaphongs, Enrico Bertini
2017	Misc	`conf`	Neural Network Word Embeddings for Text Classification of MeSH terms. AMIA Walter Wang, Yindalon Aphinyanaphongs
2017	Misc	`conf`	Optimizing Parameters of word2vec for a Text Classification Task. AMIA Vincent J. Major, Alisa Surkis, Yindalon Aphinyanaphongs
2017	J	`jnl`	Utility of general and specific word embeddings for classifying translational stages of research. CoRR Vincent J. Major, Alisa Surkis, Yindalon Aphinyanaphongs
2016	Misc	`conf`	Reusable Filtering Functions for Application in ICU data: a case study. AMIA Vincent J. Major, Monique S. Tanna, Simon Jones, Yindalon Aphinyanaphongs
2016	Misc	`conf`	Simplifying PheWAS Analysis: An R Package and Teaching Module. AMIA Emily Kawaler, Yindalon Aphinyanaphongs
2015	Misc	`conf`	Building and evaluating predictive models for postoperative ileus prior to colorectal surgery. AMIA Xuya Wang, Raul Caso Caso, Yindalon Aphinyanaphongs
2015	—	`conf`	Text Classification-Based Automatic Recruitment of Patients for Clinical Trials: A Silver Standards-Based Case Study. ICHI Bisakha Ray, Yindalon Aphinyanaphongs, Sean Heffron
2014	J	`jnl`	A comprehensive empirical comparison of modern supervised classification and feature selection methods for text categorization. J. Assoc. Inf. Sci. Technol. Yindalon Aphinyanaphongs, Lawrence D. Fu, Zhiguo Li, Eric R. Peskin, Efstratios Efstathiadis, Constantin F. Aliferis, Alexander R. Statnikov
2013	J	`jnl`	Computer models for identifying instrumental citations in the biomedical literature. Scientometrics Lawrence D. Fu, Yindalon Aphinyanaphongs, Constantin F. Aliferis
2013	Misc	`conf`	Feasibility of Machine Learning Based Automatic Classification of Medical School Curricula. AMIA Bisakha Ray, Lawrence D. Fu, William Holloway, Yindalon Aphinyanaphongs
2013	—	`conf`	Identifying Unproven Cancer Treatments on the Health Web: Addressing Accuracy, Generalizability and Scalability. MedInfo Yindalon Aphinyanaphongs, Lawrence D. Fu, Constantin F. Aliferis
2012	Misc	`conf`	Using Knowledge from APIs to Disambiguate Affiliation Names in MEDLINE. AMIA Karen Hanson, Yindalon Aphinyanaphongs, Lawrence D. Fu
2011	J	`jnl`	A comparison of evaluation metrics for biomedical journals, articles, and websites in terms of sensitivity to topic. J. Biomed. Informatics Lawrence D. Fu, Yindalon Aphinyanaphongs, Lily Wang, Constantin F. Aliferis
2007	—	`conf`	Text Categorization Models for Identifying Unproven Cancer Treatments on the Web. MedInfo Yindalon Aphinyanaphongs, Constantin F. Aliferis
2006	Misc	`conf`	Prospective Validation of Text Categorization Filters for Identifying High-Quality, Content-Specific Articles in MEDLINE. AMIA Yindalon Aphinyanaphongs, Constantin F. Aliferis
2006	J	`jnl`	Research Paper: A Comparison of Citation Metrics to Machine Learning Filters for the Identification of High Quality MEDLINE Documents. J. Am. Medical Informatics Assoc. Yindalon Aphinyanaphongs, Alexander R. Statnikov, Constantin F. Aliferis
2006	J	`jnl`	Research Paper: Using Citation Data to Improve Retrieval from MEDLINE. J. Am. Medical Informatics Assoc. Elmer V. Bernstam, Jorge R. Herskovic, Yindalon Aphinyanaphongs, Constantin F. Aliferis, Madurai G. Sriram, William R. Hersh
2005	J	`jnl`	Research Paper: Text Categorization Models for High-Quality Article Retrieval in Internal Medicine. J. Am. Medical Informatics Assoc. Yindalon Aphinyanaphongs, Ioannis Tsamardinos, Alexander R. Statnikov, Douglas P. Hardin, Constantin F. Aliferis
2003	Misc	`conf`	Text Categorization Models for Retrieval of High Quality Articles in Internal Medicine. AMIA Yindalon Aphinyanaphongs, Constantin F. Aliferis