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Challenges of Clustering Multimodal Clinical Data: Review of Applications in Asthma Subtyping

Elsie Horne, Holly Tibble, Aziz Sheikh, Athanasios Tsanas

JMIR Med Inform 2020;8(5):e16452

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Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation

Jose Juan Dominguez Veiga, Martin O'Reilly, Darragh Whelan, Brian Caulfield, Tomas E Ward

JMIR Mhealth Uhealth 2017;5(8):e115

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Data Leakage in Health Outcomes Prediction With Machine Learning. Comment on “Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning”

Applications of machine learning algorithms to predict the incidence of health outcomes have an enormous potential to improve clinical practice and lower health care costs [1].

Alexandre Chiavegatto Filho, André Filipe De Moraes Batista, Hellen Geremias dos Santos

J Med Internet Res 2021;23(2):e10969

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Detecting Motor Impairment in Early Parkinson’s Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting

Teresa Arroyo-Gallego, María J Ledesma-Carbayo, Ian Butterworth, Michele Matarazzo, Paloma Montero-Escribano, Verónica Puertas-Martín, Martha L Gray, Luca Giancardo, Álvaro Sánchez-Ferro

J Med Internet Res 2018;20(3):e89

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Comparing Precision Machine Learning With Consumer, Quality, and Volume Metrics for Ranking Orthopedic Surgery Hospitals: Retrospective Study

Dev Goyal, John Guttag, Zeeshan Syed, Rudra Mehta, Zahoor Elahi, Mohammed Saeed

J Med Internet Res 2020;22(12):e22765

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Accurate Measurement of Handwash Quality Using Sensor Armbands: Instrument Validation Study

Chaofan Wang, Zhanna Sarsenbayeva, Xiuge Chen, Tilman Dingler, Jorge Goncalves, Vassilis Kostakos

JMIR Mhealth Uhealth 2020;8(3):e17001

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Machine Learning Prediction of Foodborne Disease Pathogens: Algorithm Development and Validation Study

Hanxue Wang, Wenjuan Cui, Yunchang Guo, Yi Du, Yuanchun Zhou

JMIR Med Inform 2021;9(1):e24924

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Developing a Process for the Analysis of User Journeys and the Prediction of Dropout in Digital Health Interventions: Machine Learning Approach

Vincent Bremer, Philip I Chow, Burkhardt Funk, Frances P Thorndike, Lee M Ritterband

J Med Internet Res 2020;22(10):e17738

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Ability of Current Machine Learning Algorithms to Predict and Detect Hypoglycemia in Patients With Diabetes Mellitus: Meta-analysis

Satoru Kodama, Kazuya Fujihara, Haruka Shiozaki, Chika Horikawa, Mayuko Harada Yamada, Takaaki Sato, Yuta Yaguchi, Masahiko Yamamoto, Masaru Kitazawa, Midori Iwanaga, Yasuhiro Matsubayashi, Hirohito Sone

JMIR Diabetes 2021;6(1):e22458

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Predicting Posttraumatic Stress Disorder Risk: A Machine Learning Approach

Safwan Wshah, Christian Skalka, Matthew Price

JMIR Ment Health 2019;6(7):e13946

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