Artificial Intelligence (AI) is increasingly central to scientific research, especially in digital health and well-being. Technological advancements enable early detection of health issues and personalized treatments, facilitating real-time monitoring, promoting healthy lifestyles, and providing rehabilitation aids. The adoption of AI technologies requires reliability and promotes the development of symbiotic artificial intelligence systems, wherein humans and AI collaborate synergistically. This paper provides valuable insights into the study areas explored by our team. Our primary focus has centered on employing AI and explainable AI (XAI)-based methodologies to enable early detection and decision-making processes regarding treatments and rehabilitation for conditions such as skin melanoma, heart disease, and neurological disorders. It is crucial to recognize the importance of symbiotic systems and diagnostic support tools that rely on reliable technologies such as AI and XAI. The integration of these technologies not only improves the effectiveness of treatments and rehabilitation but also promotes greater transparency and understanding in the decision-making processes, underscoring their crucial role in the future of healthcare.

AI-driven technologies in Digital Health & Well Being: early detection and intervention strategies

Amaro I.;Auriemma Citarella A.;De Marco F.
;
Della Greca A.;Di Biasi L.;Francese R.;Rossi D.;Tortora G.;Tucci C.
2024-01-01

Abstract

Artificial Intelligence (AI) is increasingly central to scientific research, especially in digital health and well-being. Technological advancements enable early detection of health issues and personalized treatments, facilitating real-time monitoring, promoting healthy lifestyles, and providing rehabilitation aids. The adoption of AI technologies requires reliability and promotes the development of symbiotic artificial intelligence systems, wherein humans and AI collaborate synergistically. This paper provides valuable insights into the study areas explored by our team. Our primary focus has centered on employing AI and explainable AI (XAI)-based methodologies to enable early detection and decision-making processes regarding treatments and rehabilitation for conditions such as skin melanoma, heart disease, and neurological disorders. It is crucial to recognize the importance of symbiotic systems and diagnostic support tools that rely on reliable technologies such as AI and XAI. The integration of these technologies not only improves the effectiveness of treatments and rehabilitation but also promotes greater transparency and understanding in the decision-making processes, underscoring their crucial role in the future of healthcare.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4885833
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