The Technology Transfer of Machine Learning Solutions in Healthcare 4.0: The Case of Neurodegenerative Diseases
Equal last author contribution.
- DOI
- 10.2991/aisr.k.220201.003How to use a DOI?
- Keywords
- Machine Learning; Healthcare 4.0; Industry 4.0; Big Data; Magnetic Resonance Imaging
- Abstract
Along with the advancement of Machine Learning (ML) research, there is an increasing need for supporting the exploitation of ML-based solutions in a wide range of application fields of Industry 4.0. Healthcare 4.0 is one of the liveliest and interesting fields of Industry 4.0, due to the huge economic and social value of this domain. Therefore, nowadays the adoption of Technology Transfer strategies for supporting the enhancement of ML-solutions for Health 4.0 is a very relevant topic. This paper focuses some aspects related to Technology Transfer (TT) in the field of Healthcare 4.0. Artificial intelligence and machine learning are promising tools for the study of neurodegenerative diseases, which today represent a growing problem worldwide as millions of people are affected and life expectancy is increasing. The paper discusses about a pipeline implemented for neurodegenerative diseases using AI that should be valorized through a variety of complex channels in order to create value for the society and the population, by offering a new service in the field of Healthcare 4.0 based on the prediction of the most important and impactful neurodegenerative diseases, such as Alzheimer and Parkinson diseases.
- Copyright
- © 2022 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - A. Demarinis Loiotile AU - L. Bellantuono AU - F. De Nicolò AU - A. Monaco AU - S. Tangaro AU - N. Amoroso AU - R. Bellotti PY - 2022 DA - 2022/02/02 TI - The Technology Transfer of Machine Learning Solutions in Healthcare 4.0: The Case of Neurodegenerative Diseases BT - Proceedings of the 2nd International Conference on Industry 4.0 and Artificial Intelligence (ICIAI 2021) PB - Atlantis Press SP - 10 EP - 14 SN - 1951-6851 UR - https://doi.org/10.2991/aisr.k.220201.003 DO - 10.2991/aisr.k.220201.003 ID - Loiotile2022 ER -