Published on in Vol 6, No 1 (2021): Jan-Mar
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/23364, first published
.
Journals
- Jang B, Kim I. Machine-Learning Algorithms Predict Breast Cancer Patient Survival From Uk Biobank Whole-Exome Sequencing Data. Biomarkers in Medicine 2021;15(16):1529 View
- Fregoso-Aparicio L, Noguez J, Montesinos L, García-García J. Machine learning and deep learning predictive models for type 2 diabetes: a systematic review. Diabetology & Metabolic Syndrome 2021;13(1) View
- Clark S, Lomax N, Morris M, Pontin F, Birkin M. Clustering Accelerometer Activity Patterns from the UK Biobank Cohort. Sensors 2021;21(24):8220 View
- Mistry S, Riches N, Gouripeddi R, Facelli J. Environmental exposures in machine learning and data mining approaches to diabetes etiology: A scoping review. Artificial Intelligence in Medicine 2023;135:102461 View
- Atehortúa A, Gkontra P, Camacho M, Diaz O, Bulgheroni M, Simonetti V, Chadeau-Hyam M, Felix J, Sebert S, Lekadir K. Cardiometabolic risk estimation using exposome data and machine learning. International Journal of Medical Informatics 2023;179:105209 View
- Zou X, Liu Y, Ji L. Review: Machine learning in precision pharmacotherapy of type 2 diabetes—A promising future or a glimpse of hope?. DIGITAL HEALTH 2023;9 View
- Chellappan D, Rajaguru H. Detection of Diabetes through Microarray Genes with Enhancement of Classifiers Performance. Diagnostics 2023;13(16):2654 View
- Site A, Nurmi J, Lohan E. Machine-Learning-Based Diabetes Prediction Using Multisensor Data. IEEE Sensors Journal 2023;23(22):28370 View
- Bibbo D, De Marchis C, Schmid M, Ranaldi S. Machine learning to detect, stage and classify diseases and their symptoms based on inertial sensor data: a mapping review. Physiological Measurement 2023;44(12):12TR01 View
- Muse E, Topol E. Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management. Cell Metabolism 2024;36(4):670 View
- Alsadi B, Musleh S, Al-Absi H, Refaee M, Qureshi R, El Hajj N, Alam T. An ensemble-based machine learning model for predicting type 2 diabetes and its effect on bone health. BMC Medical Informatics and Decision Making 2024;24(1) View
- Rotbei S, Tseng W, Merino-Barbancho B, Haleem M, Montesinos L, Pecchia L, Fico G, Botta A. Evaluating impact of movement on diabetes via artificial intelligence and smart devices systematic literature review. Expert Systems with Applications 2024;257:125058 View
- Ali H, Niazi I, White D, Akhter M, Madanian S. Comparison of Machine Learning Models for Predicting Interstitial Glucose Using Smart Watch and Food Log. Electronics 2024;13(16):3192 View
- dos Santos M, Heckler W, Bavaresco R, Barbosa J. Machine learning applied to digital phenotyping: A systematic literature review and taxonomy. Computers in Human Behavior 2024;161:108422 View
- Serrano D, Luciano F, Anaya B, Ongoren B, Kara A, Molina G, Ramirez B, Sánchez-Guirales S, Simon J, Tomietto G, Rapti C, Ruiz H, Rawat S, Kumar D, Lalatsa A. Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine. Pharmaceutics 2024;16(10):1328 View
Books/Policy Documents
- Ibáñez-Redin G, Duarte O, Cagnani G, Oliveira O. Machine Learning for Advanced Functional Materials. View