Artificial Intelligence in Diabetes Care and Prevention

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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Improving Current Glycated Hemoglobin Prediction in Adults: Use of Machine Learning Algorithms With Electronic Health Records

Zakhriya Alhassan, Matthew Watson, David Budgen, Riyad Alshammari, Ali Alessa, Noura Al Moubayed

JMIR Med Inform 2021 (May 24); 9(5):e25237

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Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning–Based Cross-sectional Study of the UK Biobank Accelerometer Cohort

Benjamin Lam, Michael Catt, Sophie Cassidy, Jaume Bacardit, Philip Darke, Sam Butterfield, Ossama Alshabrawy, Michael Trenell, Paolo Missier

JMIR Diabetes 2021 (Mar 19); 6(1):e23364

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Machine Learning Approach to Decision Making for Insulin Initiation in Japanese Patients With Type 2 Diabetes (JDDM 58): Model Development and Validation Study

Kazuya Fujihara, Yasuhiro Matsubayashi, Mayuko Harada Yamada, Masahiko Yamamoto, Toshihiro Iizuka, Kosuke Miyamura, Yoshinori Hasegawa, Hiroshi Maegawa, Satoru Kodama, Tatsuya Yamazaki, Hirohito Sone

JMIR Med Inform 2021 (Jan 27); 9(1):e22148

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Detecting Miscoded Diabetes Diagnosis Codes in Electronic Health Records for Quality Improvement: Temporal Deep Learning Approach

Sina Rashidian, Kayley Abell-Hart, Janos Hajagos, Richard Moffitt, Veena Lingam, Victor Garcia, Chao-Wei Tsai, Fusheng Wang, Xinyu Dong, Siao Sun, Jianyuan Deng, Rajarsi Gupta, Joshua Miller, Joel Saltz, Mary Saltz

JMIR Med Inform 2020 (Dec 17); 8(12):e22649

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Predicting the Development of Type 2 Diabetes in a Large Australian Cohort Using Machine-Learning Techniques: Longitudinal Survey Study

Lei Zhang, Xianwen Shang, Subhashaan Sreedharan, Xixi Yan, Jianbin Liu, Stuart Keel, Jinrong Wu, Wei Peng, Mingguang He

JMIR Med Inform 2020 (Jul 28); 8(7):e16850

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Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists

Nicoletta Musacchio, Annalisa Giancaterini, Giacomo Guaita, Alessandro Ozzello, Maria A Pellegrini, Paola Ponzani, Giuseppina T Russo, Rita Zilich, Alberto de Micheli

J Med Internet Res 2020 (Jun 22); 22(6):e16922

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