Foundations of AI

Clinical Evidence Linkage From the American Society of Clinical Oncology 2024 Conference Poster Images Using Generative AI: Exploratory Observational Study

Carlos Areia, Michael Taylor

JMIR AI 2026 (Feb 05); 5:e78148

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Explainable AI Approaches in Federated Learning: Systematic Review

Titus Tunduny, Bernard Shibwabo

JMIR AI 2026 (Feb 03); 5:e69985

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Explainable Multitask Burnout Prediction Using Adaptive Deep Learning (EMBRACE) for Resident Physicians: Algorithm Development and Validation Study

Saima Alam, Mohammad Arif Ul Alam

JMIR AI 2026 (Jan 08); 5:e57025

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Performance of a Small Language Model Versus a Large Language Model in Answering Glaucoma Frequently Asked Patient Questions: Development and Usability Study

Adriano Cypriano Faneli, Rafael Scherer, Rohit Muralidhar, Marcus Guerreiro-Filho, Luiz Beniz, Verônica Vilasboas-Campos, Douglas Costa, Alessandro A Jammal, Felipe A Medeiros

JMIR AI 2026 (Jan 06); 5:e72101

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Authors’ Reply: Predicting the Emergency Department Patient Journey Using a Machine Learning Approach

Dhavalkumar Patel, Eyal Klang, Prem Timsina

JMIR AI 2025 (Dec 19); 4:e73342

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Predicting the Emergency Department Patient Journey Using a Machine Learning Approach

Joshua George Kovoor, Gavin John Carmichael, Brandon Stretton, Aashray K Gupta, Oliver S Kleinig, Mana Ittimani, Jack Fabian, Sheryn Tan, Jeng Swen Ng, Shrirajh Sateakeerthy, Andrew Booth, Alexander Beath, John Kefalianos, Mathew Ollapallil Jacob, Sadeya Ahmed, WengOnn Chan, Pramesh Kovoor, Samuel Gluck, Toby Gilbert, James Malycha, Benjamin A Reddi, Robert T Padbury, Markus I Trochsler, Guy J Maddern, Derek P Chew, Andrew C Zannettino, Danny Liew, John F Beltrame, Patrick G O’Callaghan, Cynthia Papendick, Stephen Bacchi

JMIR AI 2025 (Dec 19); 4:e67321

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Leveraging Smart Bed Technology to Detect COVID-19 Symptoms: Case Study

Gary Garcia-Molina, Dmytro Guzenko, Susan DeFranco, Mark Aloia, Rajasi Mills, Faisal Mushtaq, Virend K Somers

JMIR AI 2025 (Sep 17); 4:e64018

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Predicting Episodes of Hypovigilance in Intensive Care Units Using Routine Physiological Parameters and Artificial Intelligence: Derivation Study

Raphaëlle Giguère, Victor Niaussat, Monia Noël-Hunter, William Witteman, Tanya S Paul, Alexandre Marois, Philippe Després, Simon Duchesne, Patrick M Archambault

JMIR AI 2025 (Aug 27); 4:e60885

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AI-Supported Shared Decision-Making (AI-SDM): Conceptual Framework

Mohammed As'ad, Nawarh Faran, Hala Joharji

JMIR AI 2025 (Aug 07); 4:e75866

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Digital Phenotyping for Detecting Depression Severity in a Large Payor-Provider System: Retrospective Study of Speech and Language Model Performance

Bradley Karlin, Doug Henry, Ryan Anderson, Salvatore Cieri, Michael Aratow, Elizabeth Shriberg, Michelle Hoy

JMIR AI 2025 (Jun 19); 4:e69149

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Identifying Asthma-Related Symptoms From Electronic Health Records Using a Hybrid Natural Language Processing Approach Within a Large Integrated Health Care System: Retrospective Study

Fagen Xie, Robert S Zeiger, Mary Marycania Saparudin, Sahar Al-Salman, Eric Puttock, William Crawford, Michael Schatz, Stanley Xu, William M Vollmer, Wansu Chen

JMIR AI 2025 (May 02); 4:e69132

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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, Chun-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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