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Experimenting Mobile and e-Health Services with Frail MCI Older People., , , , , , and . Information, 10 (8): 253 (2019)m-Health Solutions and Data Analysis to Detect and Predict Risky and Adverse Health Conditions in Older Adults.. University of Pisa, Italy, (2021)AI-empowered m-health systems for Personalised Services and Digital Phenotyping., , and . Ital-IA, volume 3486 of CEUR Workshop Proceedings, page 217-222. CEUR-WS.org, (2023)Long-term care: how to improve the quality of life with mobile and e-health services., , , , , , and . WiMob, page 12-19. IEEE, (2018)Explainable AI for clinical and remote health applications: a survey on tabular and time series data., and . CoRR, (2022)Explainable AI for clinical and remote health applications: a survey on tabular and time series data., and . Artif. Intell. Rev., 56 (6): 5261-5315 (June 2023)Malnutrition Risk Assessment in Frail Older Adults using m-Health and Machine Learning., , and . ICC, page 1-6. IEEE, (2021)Cognitive Training and Stress Detection in MCI Frail Older People Through Wearable Sensors and Machine Learning., , and . IEEE Access, (2020)INTESA: An Integrated ICT Solution for Promoting Wellbeing in Older People., , , , , , , , , and . AI*AAL@AI*IA, volume 2061 of CEUR Workshop Proceedings, page 102-117. CEUR-WS.org, (2017)Explainable AI for Malnutrition Risk Prediction from m-Health and Clinical Data., , and . CoRR, (2023)