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Combining Unsupervised and Supervised Learning for Discovering Disease Subclasses.

, , , , and . CBMS, page 225-226. IEEE Computer Society, (2016)

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Latent Class Multi-Label Classification to Identify Subclasses of Disease for Improved Prediction., , , , , and . CBMS, page 535-538. IEEE, (2019)Predicting and Explaining Risk of Disease Worsening Using Temporal Features in Multiple Sclerosis., , , , , , and . CLEF (Working Notes), volume 3497 of CEUR Workshop Proceedings, page 1210-1218. CEUR-WS.org, (2023)V-care: An application to support lifestyle improvement in children with obesity., , , , , , and . Int. J. Medical Informatics, (September 2023)Patient-Generated Health Data Integration and Advanced Analytics for Diabetes Management: The AID-GM Platform., , , , , , , and . Sensors, 20 (1): 128 (2020)Combining Unsupervised and Supervised Learning for Discovering Disease Subclasses., , , , and . CBMS, page 225-226. IEEE Computer Society, (2016)Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review., , , , , , , , , and 15 other author(s). Artif. Intell. Medicine, (August 2023)Nearest Consensus Clustering Classification to Identify Subclasses and Predict Disease., , , , , and . J. Heal. Informatics Res., 2 (4): 402-422 (2018)Deep Learning Applied to Blood Glucose Prediction from Flash Glucose Monitoring and Fitbit Data., , , , , and . AIME, volume 12299 of Lecture Notes in Computer Science, page 59-63. Springer, (2020)