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An intelligent platform of services based on multimedia understanding and telehealth for supporting the management of SARS-CoV-2 multi-pathological patients

Conference Paper
Publication Date:
2022
abstract:
The combination of pervasive sensing and multimedia understanding with the advances in communications makes it possible to conceive platforms of services for providing telehealth solutions responding to the current needs of society. The recent outbreak has indeed posed several concerns on the management of patients at home, urging to devise complex pathways to address the Severe Acute Respiratory Syndrome (SARS) in combination with the usual diseases of an increasingly elder population. In this paper, we present TiAssisto, a project aiming to design, develop, and validate an innovative and intelligent platform of services, having as its main objective to assist both Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) multi-pathological patients and healthcare professionals. This is achieved by researching and validating new methods to improve their lives and reduce avoidable hospitalisations. TiAssisto features telehealth and telemedicine solutions to enable high-quality standards treatments based on Information and Communication Technologies (ICT), Artificial Intelligence (AI) and Machine Learning (ML). Three hundred patients are involvedin our study: one half using our telehealth platform, while the other half participate as a control group for a correct validation. The developed AI models and the Decision Support System assist General Practitioners (GPs) and other healthcare professionals in order to help them in their diagnosis, by providing suggestions and pointing out possible presence or absence of signs that can be related to pathologies. Deep learning techniques are also used to detect the absence or presence of specific signs in lung ultrasound images.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Telemedicine; Multi-pathology-and-Multi-parametric-Monitoring; Artificial-Intelligence; Machine-Learning; Decision-Support-System; Point-of-care-devices
List of contributors:
Benassi, Antonio; D'Angelo, Gennaro; Bruno, Antonio; Ignesti, Giacomo; Martinelli, Massimo; Pratali, Lorenza; Moroni, Davide; Tampucci, Marco; Galesi, Giulio; Pardini, Francesca; Bastiani, Luca; Salvetti, Ovidio
Authors of the University:
BASTIANI LUCA
GALESI GIULIO
MARTINELLI MASSIMO
MORONI DAVIDE
PARDINI FRANCESCA
PRATALI LORENZA
TAMPUCCI MARCO
Handle:
https://iris.cnr.it/handle/20.500.14243/415384
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/415384/162852/prod_471254-doc_191327.pdf
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URL

https://ieeexplore.ieee.org/document/10090211
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