Artificial Intelligence in Diabetes Care and Prevention

Machine Learning–Based Prediction of Neurodegenerative Disease in Patients With Type 2 Diabetes by Derivation and Validation in 2 Independent Korean Cohorts: Model Development and Validation Study

Hyunji Sang, Hojae Lee, Jaeyu Park, Sunyoung Kim, Ho Geol Woo, Ai Koyanagi, Lee Smith, Sihoon Lee, You-Cheol Hwang, Tae Sun Park, Hyunjung Lim, Dong Keon Yon, Sang Youl Rhee

J Med Internet Res 2024 (Oct 03); 26:e56922

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Game-Based Assessment of Peripheral Neuropathy Combining Sensor-Equipped Insoles, Video Games, and AI: Proof-of-Concept Study

Antao Ming, Vera Clemens, Elisabeth Lorek, Janina Wall, Ahmad Alhajjar, Imke Galazky, Anne-Katrin Baum, Yang Li, Meng Li, Sebastian Stober, Nils David Mertens, Peter Rene Mertens

J Med Internet Res 2024 (Oct 01); 26:e52323

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Assessment of Clinical Metadata on the Accuracy of Retinal Fundus Image Labels in Diabetic Retinopathy in Uganda: Case-Crossover Study Using the Multimodal Database of Retinal Images in Africa

Simon Arunga, Katharine Elise Morley, Teddy Kwaga, Michael Gerard Morley, Luis Filipe Nakayama, Rogers Mwavu, Fred Kaggwa, Julius Ssempiira, Leo Anthony Celi, Jessica E Haberer, Celestino Obua

JMIR Form Res 2024 (Sep 18); 8:e59914

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Machine Learning–Based Hyperglycemia Prediction: Enhancing Risk Assessment in a Cohort of Undiagnosed Individuals

Kolapo Oyebola, Funmilayo Ligali, Afolabi Owoloye, Blessing Erinwusi, Yetunde Alo, Adesola Z Musa, Oluwagbemiga Aina, Babatunde Salako

JMIRx Med 2024 (Sep 11); 5:e56993

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Implementation of Artificial Intelligence–Based Diabetic Retinopathy Screening in a Tertiary Care Hospital in Quebec: Prospective Validation Study

Fares Antaki, Imane Hammana, Marie-Catherine Tessier, Andrée Boucher, Maud Laurence David Jetté, Catherine Beauchemin, Karim Hammamji, Ariel Yuhan Ong, Marc-André Rhéaume, Danny Gauthier, Mona Harissi-Dagher, Pearse A Keane, Alfons Pomp

JMIR Diabetes 2024 (Sep 03); 9:e59867

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A Machine Learning Model for Risk Stratification of Postdiagnosis Diabetic Ketoacidosis Hospitalization in Pediatric Type 1 Diabetes: Retrospective Study

Devika Subramanian, Rona Sonabend, Ila Singh

JMIR Diabetes 2024 (Aug 07); 9:e53338

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AI Hesitancy and Acceptability—Perceptions of AI Chatbots for Chronic Health Management and Long COVID Support: Survey Study

Philip Fei Wu, Charlotte Summers, Arjun Panesar, Amit Kaura, Li Zhang

JMIR Hum Factors 2024 (Jul 23); 11:e51086

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A Comprehensive Youth Diabetes Epidemiological Data Set and Web Portal: Resource Development and Case Studies

Catherine McDonough, Yan Chak Li, Nita Vangeepuram, Bian Liu, Gaurav Pandey

JMIR Public Health Surveill 2024 (Jul 02); 10:e53330

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Generalization of a Deep Learning Model for Continuous Glucose Monitoring–Based Hypoglycemia Prediction: Algorithm Development and Validation Study

Jian Shao, Ying Pan, Wei-Bin Kou, Huyi Feng, Yu Zhao, Kaixin Zhou, Shao Zhong

JMIR Med Inform 2024 (May 24); 12:e56909

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Proactive Identification of Patients with Diabetes at Risk of Uncontrolled Outcomes during a Diabetes Management Program: Conceptualization and Development Study Using Machine Learning

Arash Khalilnejad, Ruo-Ting Sun, Tejaswi Kompala, Stefanie Painter, Roberta James, Yajuan Wang

JMIR Form Res 2024 (Apr 26); 8:e54373

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Implementation of an Electronic Clinical Decision Support System for the Early Recognition and Management of Dysglycemia in an Inpatient Mental Health Setting Using CogStack: Protocol for a Pilot Hybrid Type 3 Effectiveness-Implementation Randomized Controlled Cluster Trial

Dipen Patel, Yamiko Joseph Msosa, Tao Wang, Julie Williams, Omar G Mustafa, Siobhan Gee, Barbara Arroyo, Damian Larkin, Trevor Tiedt, Angus Roberts, Richard J B Dobson, Fiona Gaughran

JMIR Res Protoc 2024 (Apr 05); 13:e49548

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Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites

Feng He, Clarissa Ng Yin Ling, Simon Nusinovici, Ching-Yu Cheng, Tien Yin Wong, Jialiang Li, Charumathi Sabanayagam

J Med Internet Res 2024 (Mar 28); 26:e41065

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Acceptability of Mobile App–Based Motivational Interviewing and Preferences for App Features to Support Self-Management in Patients With Type 2 Diabetes: Qualitative Study

Sungwon Yoon, Haoming Tang, Chao Min Tan, Jie Kie Phang, Yu Heng Kwan, Lian Leng Low

JMIR Diabetes 2024 (Mar 06); 9:e48310

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A Mobile App That Addresses Interpretability Challenges in Machine Learning–Based Diabetes Predictions: Survey-Based User Study

Rasha Hendawi, Juan Li, Souradip Roy

JMIR Form Res 2023 (Nov 13); 7:e50328

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An “All-Data-on-Hand” Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study

David D Williams, Diana Ferro, Colin Mullaney, Lydia Skrabonja, Mitchell S Barnes, Susana R Patton, Brent Lockee, Erin M Tallon, Craig A Vandervelden, Cintya Schweisberger, Sanjeev Mehta, Ryan McDonough, Marcus Lind, Leonard D'Avolio, Mark A Clements

JMIR Diabetes 2023 (Jul 18); 8:e47592

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Optimizing Health Coaching for Patients With Type 2 Diabetes Using Machine Learning: Model Development and Validation Study

Shuang Di, Jeremy Petch, Hertzel C Gerstein, Ruoqing Zhu, Diana Sherifali

JMIR Form Res 2022 (Sep 13); 6(9):e37838

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Identifying Patients With Hypoglycemia Using Natural Language Processing: Systematic Literature Review

Yaguang Zheng, Victoria Vaughan Dickson, Saul Blecker, Jason M Ng, Brynne Campbell Rice, Gail D’Eramo Melkus, Liat Shenkar, Marie Claire R Mortejo, Stephen B Johnson

JMIR Diabetes 2022 (May 16); 7(2):e34681

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User-Centered Design of A Novel Risk Prediction Behavior Change Tool Augmented With an Artificial Intelligence Engine (MyDiabetesIQ): A Sociotechnical Systems Approach

Cathy Shields, Scott G Cunningham, Deborah J Wake, Evridiki Fioratou, Doogie Brodie, Sam Philip, Nicholas T Conway

JMIR Hum Factors 2022 (Feb 08); 9(1):e29973

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Patient-Generated Data Analytics of Health Behaviors of People Living With Type 2 Diabetes: Scoping Review

Meghan S Nagpal, Antonia Barbaric, Diana Sherifali, Plinio P Morita, Joseph A Cafazzo

JMIR Diabetes 2021 (Dec 20); 6(4):e29027

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Using a Convolutional Neural Network to Predict Remission of Diabetes After Gastric Bypass Surgery: Machine Learning Study From the Scandinavian Obesity Surgery Register

Yang Cao, Ingmar Näslund, Erik Näslund, Johan Ottosson, Scott Montgomery, Erik Stenberg

JMIR Med Inform 2021 (Aug 19); 9(8):e25612

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