Research Methodology

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Articles published in 2024 in this theme: 7 (scroll down to load remaining articles)

2024

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Machine Learning–Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation

Joshua Kuan Tan, Le Quan, Nur Nasyitah Mohamed Salim, Jen Hong Tan, Su-Yen Goh, Julian Thumboo, Yong Mong Bee

JMIR AI 2024 (Oct 17); 3:e58463

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Trial Factors Associated With Completion of Clinical Trials Evaluating AI: Retrospective Case-Control Study

David Chen, Christian Cao, Robert Kloosterman, Rod Parsa, Srinivas Raman

J Med Internet Res 2024 (Sep 23); 26:e58578

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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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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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Identifying Patterns of Smoking Cessation App Feature Use That Predict Successful Quitting: Secondary Analysis of Experimental Data Leveraging Machine Learning

Leeann Nicole Siegel, Kara P Wiseman, Alex Budenz, Yvonne Prutzman

JMIR AI 2024 (May 22); 3:e51756

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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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Research Methodology - AI

2024

Machine Learning–Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation

Trial Factors Associated With Completion of Clinical Trials Evaluating AI: Retrospective Case-Control Study

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

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

Identifying Patterns of Smoking Cessation App Feature Use That Predict Successful Quitting: Secondary Analysis of Experimental Data Leveraging Machine Learning

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

Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial