Virtual hospital and artificial intelligence: a first step towards the application of an innovative health system for the care of rare cerebrovascular diseases.

Journal: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Published Date:

Abstract

The development of virtual care options, including virtual hospital platforms, is rapidly changing the healthcare, mostly in the pandemic period, due to difficulties in in-person consultations. For this purpose, in 2020, a neurological Virtual Hospital (NOVHO) pilot study has been implemented, in order to experiment a multidisciplinary second opinion evaluation system for neurological diseases. Cerebrovascular diseases represent a preponderant part of neurological disorders. However, more than 30% of strokes remain of undetermined source, and rare CVD (rCVD) are often misdiagnosed. The lack of data on phenotype and clinical course of rCVD patients makes the diagnosis and the development of therapies challenging. Since the diagnosis and care of rCVDs require adequate expertise and instrumental tools, their management is mostly allocated to a few experienced hospitals, making difficult equity in access to care. Therefore, strategies for virtual consultations are increasingly applied with some advantage for patient management also in peripheral areas. Moreover, health data are becoming increasingly complex and require new technologies to be managed. The use of Artificial Intelligence is beginning to be applied to the healthcare system and together with the Internet of Things will enable the creation of virtual models with predictive abilities, bringing healthcare one step closer to personalized medicine. Herein, we will report on the preliminary results of the NOVHO project and present the methodology of a new project aimed at developing an innovative multidisciplinary and multicentre virtual care model, specific for rCVD (NOVHO-rCVD), which combines the virtual hospital approach and the deep-learning machine system.

Authors

  • Nicola Rifino
    Cerebrovascular Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy. nicola.rifino@istituto-besta.it.
  • Anna Bersano
    Cerebrovascular Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy.
  • Alessandro Padovani
    Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
  • Giancarlo Maria Conti
    Department of Neurology, ASST Nord Milano, Ospedale Bassini, Cinisello Balsamo, Italy.
  • Anna Cavallini
    Cerebrovascular Disease and Stroke Unit, IRCCS Fondazione Mondino, Pavia, Italy.
  • Luca Colombo
    University of Milan, Milan, Italy.
  • Alberto Priori
    Department of Neurology, Ospedale San Paolo, Milan, Italy.
  • Raffaella Pianese
    S.I.T.R.A, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
  • Maria Rosaria Gammone
    S.I.T.R.A, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
  • Alessandra Erbetta
    Service of Neuroradiology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
  • Elisa Francesca Ciceri
    Diagnostic Radiology and Interventional Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
  • Davide Sattin
    Istituti Clinici Scientifici Maugeri IRCCS Via Camaldoli 64, 20138, Milan, Italy.
  • Riccardo Varvello
    La Nava srl, Aosta, Italy.
  • Eugenio Agostino Parati
    Istituti Clinici Scientifici Maugeri IRCCS Via Camaldoli 64, 20138, Milan, Italy.
  • Emma Scelzo
    Department of Neurology, Ospedale San Paolo, Milan, Italy.