11 Sept. | ![]() |
09:00 - 10:30 |
ROOM 7 | |||||||
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YOUNGINNOVATION |
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THE STATE OF RESEARCH COMMUNICATED BY YOUNG RESEARCHERS | |||||||
TT.I - Technical Multi-Track with Parallel SYMPOSIA | |||||||
Artificial intelligence and Machine learning in digital health | |||||||
Co-organized with University Magna Graecia of Catanzaro in cooperation with SIRTEPS e SITELF Chair: Alessia BRAMANTI, University of Salerno |
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The evolution of digital technologies is opening new frontiers in healthcare, thanks to the integration of Artificial Intelligence (AI) and Machine Learning. These powerful technologies are tackling complex medical challenges and transforming the healthcare field into a new era of more accurate diagnoses, personalized therapies, and proactive health management. From early disease detection to individual risk prediction, these technologies are proving to be fundamental tools for enhancing the precision and effectiveness of treatments. In detail, AI is revolutionizing the collection and analysis of clinical data, enabling the identification of hidden patterns and correlations that would escape human observation. On the other hand, Machine Learning is refining predictions of medical outcomes and facilitating continuous patient monitoring through digital devices and wearables. The link between AI, Machine Learning, and Digital Health not only promises improvements in timely diagnoses and prognosis, but also offers innovative solutions for managing large volumes of medical data, discovering new drugs, and personalized therapies. However, this revolution is not without challenges, such as ethical dilemmas related to patient data usage and the implementation of decision-making algorithms in healthcare. Balancing technological innovation with privacy and medical responsibility is a crucial theme that requires attention. |
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The symposium is part of the SE.I |
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TT.I.I.1 SE.I.2.1 |
Introductive Keynote Giuseppe SCANNIELLO - CV University of Salerno Application of artificial intelligence and machine learning in cardiovascular diseases |
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TT.I.I.2 SE.I.2.2 |
Chiara CAMASTRA - CV University of Catanzaro "Magna Graecia" Exploring sex-based brain morphometry differences through Explainable Artificial Intelligence: insights for digital health innovation |
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TT.I.I.3 SE.I.2.3 |
Marina GAROFANO - CV University of Salerno Use of new technologies in physiotherapy in defining the therapeutic exercise dose |
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TT.I.I.4 SE.I.2.4 |
Assunta PELAGI - CV University of Catanzaro "Magna Graecia" Predicting and understanding psychological well-being in young adult: new insight for digital health |
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TT.I.I.5 SE.I.2.5 |
Luca BARILLARO - CV University of Catanzaro "Magna Graecia" Scalable deep learning: Applications in medicine |
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