In just a few months’ time, the COVID-19 crisis has accelerated the digitization in all sectors, including healthcare. Cutting-edge technological tools and innovations are increasingly adopted in all areas of public health, medicine and wellbeing. Digital health ecosystems allow the shift from an organization-centric to a patient-centric model of delivering healthcare services.1 In addition to traditional methods,2 robotics, artificial intelligence (AI), big data analytics, wearable devices, mobile applications (apps) and tele-medicine become effective resources.3 Some examples of recent developments include automated and standardized analysis and software tools using AI for visualization and quantification of radiological images; low-dose-computedtomography for monitoring interstitial lung diseases (ILD) with lower radiation dose; combined deep learning (DL) and machine learning algorithms able to distinguish idiopathic pulmonary fibrosis among various ILDs4–6; DL algorithms to predict survival in intensive care unit (ICU)7 ; robotic bronchoscopy showing promising results especially when combined with advanced imaging.8 We have the technology to monitor chest wall motion providing informationonrespiratorymuscles actionandoncritical vital signs, like respiration and cardiac activity and manage at distance the impairment in physical performance with appropriate programs of tele-rehabilitation.

Use of Technology in Respiratory Medicine

Aliverti A.
2023-01-01

Abstract

In just a few months’ time, the COVID-19 crisis has accelerated the digitization in all sectors, including healthcare. Cutting-edge technological tools and innovations are increasingly adopted in all areas of public health, medicine and wellbeing. Digital health ecosystems allow the shift from an organization-centric to a patient-centric model of delivering healthcare services.1 In addition to traditional methods,2 robotics, artificial intelligence (AI), big data analytics, wearable devices, mobile applications (apps) and tele-medicine become effective resources.3 Some examples of recent developments include automated and standardized analysis and software tools using AI for visualization and quantification of radiological images; low-dose-computedtomography for monitoring interstitial lung diseases (ILD) with lower radiation dose; combined deep learning (DL) and machine learning algorithms able to distinguish idiopathic pulmonary fibrosis among various ILDs4–6; DL algorithms to predict survival in intensive care unit (ICU)7 ; robotic bronchoscopy showing promising results especially when combined with advanced imaging.8 We have the technology to monitor chest wall motion providing informationonrespiratorymuscles actionandoncritical vital signs, like respiration and cardiac activity and manage at distance the impairment in physical performance with appropriate programs of tele-rehabilitation.
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1235365
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