The CoViD-19 pandemic generated huge quantities of healthcare and clinical data. Artificial intelligence (AI) may help in processing such data, to support patient care, and to plan healthcare actions for pandemic control. This paper aims at analyzing the state of the art of AI and Clinical Information Systems to support the management of CoViD-19 patients. The analysis is performed according to a proposed taxonomy based on methodologies and techniques, and it also discusses some research directions. We consider and extend some recent taxonomies, for classifying intelligent information systems and Artificial Intelligence techniques for data-intensive applications. We consider methodologies and techniques for CoViD-19 pandemic data analysis. We describe the state of the art, according to the proposed taxonomy, i.e., data collection, machine learning, natural language processing, process mining and pathway identification, decision support systems. We analyze and highlight some emerging directions for shortand mid-term research activities.

Health Informatics: Clinical Information Systems and Artificial Intelligence to Support Medicine in the CoViD-19 Pandemic

Combi, Carlo;Pozzi, Giuseppe
2021

Abstract

The CoViD-19 pandemic generated huge quantities of healthcare and clinical data. Artificial intelligence (AI) may help in processing such data, to support patient care, and to plan healthcare actions for pandemic control. This paper aims at analyzing the state of the art of AI and Clinical Information Systems to support the management of CoViD-19 patients. The analysis is performed according to a proposed taxonomy based on methodologies and techniques, and it also discusses some research directions. We consider and extend some recent taxonomies, for classifying intelligent information systems and Artificial Intelligence techniques for data-intensive applications. We consider methodologies and techniques for CoViD-19 pandemic data analysis. We describe the state of the art, according to the proposed taxonomy, i.e., data collection, machine learning, natural language processing, process mining and pathway identification, decision support systems. We analyze and highlight some emerging directions for shortand mid-term research activities.
978-1-6654-0132-6
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11562/1073849
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