Yindalon Aphinyanagphongs

According to our database, Yindalon Aphinyanagphongs authored at least 56 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

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

Seeing Beyond Borders: Evaluating LLMs in Multilingual Ophthalmological Question Answering.

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

Proceedings of the 12th IEEE International Conference on Healthcare Informatics, 2024

NYULangone at Chemotimelines 2024: Utilizing Open-Weights Large Language Models for Chemotherapy Event Extraction.

Jeff Zhang, Yin Aphinyanaphongs, Anthony Cardillo

Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024

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, 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

Nat., 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

Diagnosis Uncertain Models For Medical Risk Prediction.

Alexander Peysakhovich, Rich Caruana, Yin Aphinyanaphongs

CoRR, 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, Nicholas Kiefer, Nathaniel Smilowitz, James Horowitz, Tania Ahuja, Glenn I Fishman, Judith Hochman, Stuart Katz, Samuel Bernard, Rajesh Ranganath

CoRR, 2023

Enabling AI-Augmented Clinical Workflows by Accessing Patient Data in Real-Time with FHIR.

Vincent J. Major, Walter Wang, Yindalon Aphinyanaphongs

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

Ten Years of Health Informatics Education for Physicians.

Vincent J. Major, Claudia S. Plottel, Yindalon Aphinyanaphongs

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

2022

AI model transferability in healthcare: a sociotechnical perspective.

Batia Mishan Wiesenfeld, Yin Aphinyanaphongs, Oded Nov

Nat. Mac. Intell., October, 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., May, 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

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

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

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

Proceedings of the AMIA 2022, 2022

2021

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

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

npj Digit. Medicine, 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

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

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

Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, 2021

Prediction of Resuscitation for Pediatric Sepsis from Data Available at Triage.

Peter A. Stella, Elizabeth Haines, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Data-Driven Patterns in Protective Effects of Ibuprofen and Ketorolac on Hospitalized Covid-19 Patients.

Rich Caruana, Benjamin J. Lengerich, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations.

Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

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, 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

npj Digit. Medicine, 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

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

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

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

CoRR, 2020

Assessment of Amazon Comprehend Medical: Medication Information Extraction.

Benedict Guzman, Isabel Metzger, Yindalon Aphinyanaphongs, Himanshu Grover

CoRR, 2020

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

Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task, 2020

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

Proceedings of the AMIA 2019, 2019

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

Proceedings of the AMIA 2019, 2019

2018

Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research.

Vincent J. Major, Alisa Surkis, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2018, 2018

2017

A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations.

Josua Krause, Aritra Dasgupta, Jordan Swartz, Yindalon Aphinyanaphongs, Enrico Bertini

Proceedings of the 12th IEEE Conference on Visual Analytics Science and Technology, 2017

Neural Network Word Embeddings for Text Classification of MeSH terms.

Walter Wang, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2017, 2017

Optimizing Parameters of word2vec for a Text Classification Task.

Vincent J. Major, Alisa Surkis, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2017, 2017

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

Proceedings of the AMIA 2017, 2017

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

Proceedings of the Biocomputing 2016: Proceedings of the Pacific Symposium, 2016

Reusable Filtering Functions for Application in ICU data: a case study.

Vincent J. Major, Monique S. Tanna, Simon Jones, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2016, 2016

Simplifying PheWAS Analysis: An R Package and Teaching Module.

Emily Kawaler, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2016, 2016

2015

Text Classification-Based Automatic Recruitment of Patients for Clinical Trials: A Silver Standards-Based Case Study.

Bisakha Ray, Yindalon Aphinyanaphongs, Sean Heffron

Proceedings of the 2015 International Conference on Healthcare Informatics, 2015

Building and evaluating predictive models for postoperative ileus prior to colorectal surgery.

Xuya Wang, Raul Caso Caso, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2015, 2015

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

Text classification for automatic detection of alcohol use-related tweets: A feasibility study.

Yin Aphinyanaphongs, Bisakha Ray, Alexander R. Statnikov, Paul Krebs

Proceedings of the 15th IEEE International Conference on Information Reuse and Integration, 2014

2013

Computer models for identifying instrumental citations in the biomedical literature.

Lawrence D. Fu, Yindalon Aphinyanaphongs, Constantin F. Aliferis

Scientometrics, 2013

Identifying Unproven Cancer Treatments on the Health Web: Addressing Accuracy, Generalizability and Scalability.

Yindalon Aphinyanaphongs, Lawrence D. Fu, Constantin F. Aliferis

Proceedings of the MEDINFO 2013, 2013

Feasibility of Machine Learning Based Automatic Classification of Medical School Curricula.

Bisakha Ray, Lawrence D. Fu, William Holloway, Yindalon Aphinyanaphongs

Proceedings of the AMIA 2013, 2013

2012

Using Knowledge from APIs to Disambiguate Affiliation Names in MEDLINE.

Karen Hanson, Yindalon Aphinyanaphongs, Lawrence D. Fu

Proceedings of the AMIA 2012, 2012

2011

A comparison of evaluation metrics for biomedical journals, articles, and websites in terms of sensitivity to topic.

Lawrence D. Fu, Yindalon Aphinyanaphongs, Lily Wang, Constantin F. Aliferis

J. Biomed. Informatics, 2011

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, Yindalon Aphinyanagphongs, Constantin F. Aliferis

Proceedings of the MEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics, 2007

Text Categorization Models for Identifying Unproven Cancer Treatments on the Web.

Yindalon Aphinyanaphongs, Constantin F. Aliferis

Proceedings of the MEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics, 2007

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

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

Prospective Validation of Text Categorization Filters for Identifying High-Quality, Content-Specific Articles in MEDLINE.

Yindalon Aphinyanaphongs, Constantin F. Aliferis

Proceedings of the AMIA 2006, 2006

2005

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

2004

Learning Boolean Queries for Article Quality Filtering.

Yin Aphinyanaphongs, Constantin F. Aliferis

Proceedings of the MEDINFO 2004, 2004

2003

Text Categorization Models for Retrieval of High Quality Articles in Internal Medicine.

Yindalon Aphinyanaphongs, Constantin F. Aliferis

Proceedings of the AMIA 2003, 2003