2024

Learning From International Comparators of National Medical Imaging Initiatives for AI Development: Multiphase Qualitative Study

Kassandra Karpathakis, Emma Pencheon, Dominic Cushnan

JMIR AI 2024 (Jan 04); 3:e51168

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Predictive Performance of Machine Learning–Based Models for Poststroke Clinical Outcomes in Comparison With Conventional Prognostic Scores: Multicenter, Hospital-Based Observational Study

Fumi Irie, Koutarou Matsumoto, Ryu Matsuo, Yasunobu Nohara, Yoshinobu Wakisaka, Tetsuro Ago, Naoki Nakashima, Takanari Kitazono, Masahiro Kamouchi

JMIR AI 2024 (Jan 11); 3:e46840

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Identifying Symptoms Prior to Pancreatic Ductal Adenocarcinoma Diagnosis in Real-World Care Settings: Natural Language Processing Approach

Fagen Xie, Jenny Chang, Tiffany Luong, Bechien Wu, Eva Lustigova, Eva Shrader, Wansu Chen

JMIR AI 2024 (Jan 15); 3:e51240

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Sepsis Prediction at Emergency Department Triage Using Natural Language Processing: Retrospective Cohort Study

Felix Brann, Nicholas William Sterling, Stephanie O Frisch, Justin D Schrager

JMIR AI 2024 (Jan 25); 3:e49784

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Identifying Frailty in Older Adults Receiving Home Care Assessment Using Machine Learning: Longitudinal Observational Study on the Role of Classifier, Feature Selection, and Sample Size

Cheng Pan, Hao Luo, Gary Cheung, Huiquan Zhou, Reynold Cheng, Sarah Cullum, Chuan Wu

JMIR AI 2024 (Jan 31); 3:e44185

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Assessment of ChatGPT-3.5's Knowledge in Oncology: Comparative Study with ASCO-SEP Benchmarks

Roupen Odabashian, Donald Bastin, Georden Jones, Maria Manzoor, Sina Tangestaniapour, Malke Assad, Sunita Lakhani, Maritsa Odabashian, Sharon McGee

JMIR AI 2024 (Jan 12); 3:e50442

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Health Care Professionals’ and Parents’ Perspectives on the Use of AI for Pain Monitoring in the Neonatal Intensive Care Unit: Multisite Qualitative Study

Nicole Racine, Cheryl Chow, Lojain Hamwi, Oana Bucsea, Carol Cheng, Hang Du, Lorenzo Fabrizi, Sara Jasim, Lesley Johannsson, Laura Jones, Maria Pureza Laudiano-Dray, Judith Meek, Neelum Mistry, Vibhuti Shah, Ian Stedman, Xiaogang Wang, Rebecca Pillai Riddell

JMIR AI 2024 (Feb 09); 3:e51535

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Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study

Danissa V Rodriguez, Ji Chen, Ratnalekha V N Viswanadham, Katharine Lawrence, Devin Mann

JMIR AI 2024 (Mar 01); 3:e47122

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Risk Perception, Acceptance, and Trust of Using AI in Gastroenterology Practice in the Asia-Pacific Region: Web-Based Survey Study

Wilson WB Goh, Kendrick YA Chia, Max FK Cheung, Kalya M Kee, May O Lwin, Peter J Schulz, Minhu Chen, Kaichun Wu, Simon SM Ng, Rashid Lui, Tiing Leong Ang, Khay Guan Yeoh, Han-mo Chiu, Deng-chyang Wu, Joseph JY Sung

JMIR AI 2024 (Mar 07); 3:e50525

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Machine Learning Methods Using Artificial Intelligence Deployed on Electronic Health Record Data for Identification and Referral of At-Risk Patients From Primary Care Physicians to Eye Care Specialists: Retrospective, Case-Controlled Study

Joshua A Young, Chin-Wen Chang, Charles W Scales, Saurabh V Menon, Chantal E Holy, Caroline Adrienne Blackie

JMIR AI 2024 (Mar 12); 3:e48295

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The Impact of Expectation Management and Model Transparency on Radiologists’ Trust and Utilization of AI Recommendations for Lung Nodule Assessment on Computed Tomography: Simulated Use Study

Lotte J S Ewals, Lynn J J Heesterbeek, Bin Yu, Kasper van der Wulp, Dimitrios Mavroeidis, Mathias Funk, Chris C P Snijders, Igor Jacobs, Joost Nederend, Jon R Pluyter, e/MTIC Oncology group

JMIR AI 2024 (Mar 13); 3:e52211

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What Is the Performance of ChatGPT in Determining the Gender of Individuals Based on Their First and Last Names?

Paul Sebo

JMIR AI 2024 (Mar 13); 3:e53656

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Reidentification of Participants in Shared Clinical Data Sets: Experimental Study

Daniela Wiepert, Bradley A Malin, Joseph R Duffy, Rene L Utianski, John L Stricker, David T Jones, Hugo Botha

JMIR AI 2024 (Mar 15); 3:e52054

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Perceptions of Family Physicians About Applying AI in Primary Health Care: Case Study From a Premier Health Care Organization

Muhammad Atif Waheed, Lu Liu

JMIR AI 2024 (Apr 17); 3:e40781

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Identifying Links Between Productivity and Biobehavioral Rhythms Modeled From Multimodal Sensor Streams: Exploratory Quantitative Study

Runze Yan, Xinwen Liu, Janine M Dutcher, Michael J Tumminia, Daniella Villalba, Sheldon Cohen, John D Creswell, Kasey Creswell, Jennifer Mankoff, Anind K Dey, Afsaneh Doryab

JMIR AI 2024 (Apr 18); 3:e47194

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Role of Ethics in Developing AI-Based Applications in Medicine: Insights From Expert Interviews and Discussion of Implications

Lukas Weidener, Michael Fischer

JMIR AI 2024 (Jan 12); 3:e51204

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Beyond the Hype—The Actual Role and Risks of AI in Today’s Medical Practice: Comparative-Approach Study

Steffan Hansen, Carl Joakim Brandt, Jens Søndergaard

JMIR AI 2024 (Jan 22); 3:e49082

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An Environmental Uncertainty Perception Framework for Misinformation Detection and Spread Prediction in the COVID-19 Pandemic: Artificial Intelligence Approach

Jiahui Lu, Huibin Zhang, Yi Xiao, Yingyu Wang

JMIR AI 2024 (Jan 29); 3:e47240

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Correction: Using Conversational AI to Facilitate Mental Health Assessments and Improve Clinical Efficiency Within Psychotherapy Services: Real-World Observational Study

Max Rollwage, Johanna Habicht, Keno Juechems, Ben Carrington, Sruthi Viswanathan, Mona Stylianou, Tobias U Hauser, Ross Harper

JMIR AI 2024 (Mar 12); 3:e57869

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Privacy-Preserving Federated Survival Support Vector Machines for Cross-Institutional Time-To-Event Analysis: Algorithm Development and Validation

Julian Späth, Zeno Sewald, Niklas Probul, Magali Berland, Mathieu Almeida, Nicolas Pons, Emmanuelle Le Chatelier, Pere Ginès, Cristina Solé, Adrià Juanola, Josch Pauling, Jan Baumbach

JMIR AI 2024 (Mar 29); 3:e47652

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