Caiffa, Arianna (A.A. 2023/2024) Smarth Health: exploiting AI to analyze microchip and sensor data. Tesi di Laurea in Big data and smart data analytics, Luiss Guido Carli, relatore Irene Finocchi, pp. 43. [Master's Degree Thesis]

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Abstract/Index

AI-driven personalized medicine: ethical, privacy and data analysis perspectives. Personalized medicine and the role of AI. Ethics and privacy in the era of connected health: crucial considerations. AI analysis of microchip and sensor data. Theoretical foundations. Subcutaneous microchips and sensors: pioneers in health surveillance. Exploring V-LAP and other advanced internal sensors. Detecting human activities through deep learning approaches. Experimental data analysis. Health datamining: data collection methodology. Coding in health: programming tools for advanced analysis. Potential future developments in AI integration in health.

References

Bibliografia: pp. 39-43.

Thesis Type:	Master's Degree Thesis
Institution:	Luiss Guido Carli
Degree Program:	Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91)
Chair:	Big data and smart data analytics
Thesis Supervisor:	Finocchi, Irene
Thesis Co-Supervisor:	Sinaimeri, Blerina
Academic Year:	2023/2024
Session:	Summer
Deposited by:	Alessandro Perfetti
Date Deposited:	17 Dec 2024 15:28
Last Modified:	17 Dec 2024 15:28
URI:	https://tesi.luiss.it/id/eprint/40677

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