Foundations of AI

Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis

De Rong Loh, Elliot D Hill, Nan Liu, Geraldine Dawson, Matthew M Engelhard

JMIR AI 2025 (Mar 27); 4:e62985

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Estimation of Static Lung Volumes and Capacities From Spirometry Using Machine Learning: Algorithm Development and Validation

Scott A Helgeson, Zachary S Quicksall, Patrick W Johnson, Kaiser G Lim, Rickey E Carter, Augustine S Lee

JMIR AI 2025 (Mar 24); 4:e65456

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Using AI to Translate and Simplify Spanish Orthopedic Medical Text: Instrument Validation Study

Saman Andalib, Aidin Spina, Bryce Picton, Sean S Solomon, John A Scolaro, Ariana M Nelson

JMIR AI 2025 (Mar 21); 4:e70222

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Improving the Robustness and Clinical Applicability of Automatic Respiratory Sound Classification Using Deep Learning–Based Audio Enhancement: Algorithm Development and Validation

Jing-Tong Tzeng, Jeng-Lin Li, Huan-Yu Chen, Chu-Hsiang Huang, Chi-Hsin Chen, Cheng-Yi Fan, Edward Pei-Chuan Huang, Chi-Chun Lee

JMIR AI 2025 (Mar 13); 4:e67239

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Deep Learning Models to Predict Diagnostic and Billing Codes Following Visits to a Family Medicine Practice: Development and Validation Study

Akshay Rajaram, Michael Judd, David Barber

JMIR AI 2025 (Mar 07); 4:e64279

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Targeting COVID-19 and Human Resources for Health News Information Extraction: Algorithm Development and Validation

Mathieu Ravaut, Ruochen Zhao, Duy Phung, Vicky Mengqi Qin, Dusan Milovanovic, Anita Pienkowska, Iva Bojic, Josip Car, Shafiq Joty

JMIR AI 2024 (Oct 30); 3:e55059

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Development of Lung Cancer Risk Prediction Machine Learning Models for Equitable Learning Health System: Retrospective Study

Anjun Chen, Erman Wu, Ran Huang, Bairong Shen, Ruobing Han, Jian Wen, Zhiyong Zhang, Qinghua Li

JMIR AI 2024 (Sep 11); 3:e56590

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Near Real-Time Syndromic Surveillance of Emergency Department Triage Texts Using Natural Language Processing: Case Study in Febrile Convulsion Detection

Sedigh Khademi, Christopher Palmer, Muhammad Javed, Gerardo Luis Dimaguila, Hazel Clothier, Jim Buttery, Jim Black

JMIR AI 2024 (Aug 30); 3:e54449

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Obtaining the Most Accurate, Explainable Model for Predicting Chronic Obstructive Pulmonary Disease: Triangulation of Multiple Linear Regression and Machine Learning Methods

Arnold Kamis, Nidhi Gadia, Zilin Luo, Shu Xin Ng, Mansi Thumbar

JMIR AI 2024 (Aug 29); 3:e58455

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Traditional Machine Learning, Deep Learning, and BERT (Large Language Model) Approaches for Predicting Hospitalizations From Nurse Triage Notes: Comparative Evaluation of Resource Management

Dhavalkumar Patel, Prem Timsina, Larisa Gorenstein, Benjamin S Glicksberg, Ganesh Raut, Satya Narayan Cheetirala, Fabio Santana, Jules Tamegue, Arash Kia, Eyal Zimlichman, Matthew A Levin, Robert Freeman, Eyal Klang

JMIR AI 2024 (Aug 27); 3:e52190

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Mitigating Sociodemographic Bias in Opioid Use Disorder Prediction: Fairness-Aware Machine Learning Framework

Mohammad Yaseliani, Md Noor-E-Alam, Md Mahmudul Hasan

JMIR AI 2024 (Aug 20); 3:e55820

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Predicting Workers’ Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics

Hiroki Iwamoto, Saki Nakano, Ryotaro Tajima, Ryo Kiguchi, Yuki Yoshida, Yoshitake Kitanishi, Yasunori Aoki

JMIR AI 2024 (Aug 02); 3:e55840

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Optimizing Clinical Trial Eligibility Design Using Natural Language Processing Models and Real-World Data: Algorithm Development and Validation

Kyeryoung Lee, Zongzhi Liu, Yun Mai, Tomi Jun, Meng Ma, Tongyu Wang, Lei Ai, Ediz Calay, William Oh, Gustavo Stolovitzky, Eric Schadt, Xiaoyan Wang

JMIR AI 2024 (Jul 29); 3:e50800

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Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development

Hisashi Kurasawa, Kayo Waki, Tomohisa Seki, Akihiro Chiba, Akinori Fujino, Katsuyoshi Hayashi, Eri Nakahara, Tsuneyuki Haga, Takashi Noguchi, Kazuhiko Ohe

JMIR AI 2024 (Jul 18); 3:e56700

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Multiscale Bowel Sound Event Spotting in Highly Imbalanced Wearable Monitoring Data: Algorithm Development and Validation Study

Annalisa Baronetto, Luisa Graf, Sarah Fischer, Markus F Neurath, Oliver Amft

JMIR AI 2024 (Jul 10); 3:e51118

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Augmenting Telepostpartum Care With Vision-Based Detection of Breastfeeding-Related Conditions: Algorithm Development and Validation

Jessica De Souza, Varun Kumar Viswanath, Jessica Maria Echterhoff, Kristina Chamberlain, Edward Jay Wang

JMIR AI 2024 (Jun 24); 3:e54798

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Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic and Personalized Modeling

Tahsin Mullick, Sam Shaaban, Ana Radovic, Afsaneh Doryab

JMIR AI 2024 (May 20); 3:e47805

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Improving Risk Prediction of Methicillin-Resistant Staphylococcus aureus Using Machine Learning Methods With Network Features: Retrospective Development Study

Methun Kamruzzaman, Jack Heavey, Alexander Song, Matthew Bielskas, Parantapa Bhattacharya, Gregory Madden, Eili Klein, Xinwei Deng, Anil Vullikanti

JMIR AI 2024 (May 16); 3:e48067

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Sample Size Considerations for Fine-Tuning Large Language Models for Named Entity Recognition Tasks: Methodological Study

Zoltan P Majdik, S Scott Graham, Jade C Shiva Edward, Sabrina N Rodriguez, Martha S Karnes, Jared T Jensen, Joshua B Barbour, Justin F Rousseau

JMIR AI 2024 (May 16); 3:e52095

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A Comparison of Personalized and Generalized Approaches to Emotion Recognition Using Consumer Wearable Devices: Machine Learning Study

Joe Li, Peter Washington

JMIR AI 2024 (May 10); 3:e52171

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