Foundations of AI

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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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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