Drug repositioning to combat COVID-19 using artificial intelligence system

Abstract Background Vascular angiopathy is suggested to be the major cause of silent hypoxia among COVID-19 patients without severe parenchymal involvement. However, pulmonologists and clinicians in intensive care units become confused when they encounter acute respiratory deterioration with neither severe parenchymal lung involvement nor acute pulmonary embolism. Other radiological vascular signs might solve this confusion. This study investigated other indirect vascular angiopathy signs on CT pulmonary angiography (CTPA) and involved a novel statistical analysis that was performed to determine the significance of associations between these signs and the CT opacity score of the pathological lung volume, which is calculated by an artificial intelligence system. Results The study was conducted retrospectively, during September and October 2020, on 73 patients with critical COVID-19 who were admitted to the ICU with progressive dyspnea and low O2 saturation on room air (PaO2 < 93%). They included 53 males and 20 females (73%:27%), and their age ranged from 18 to 88 years (mean ± SD=53.3 ± 13.5). CT-pulmonary angiography was performed for all patients, and an artificial intelligence system was utilized to quantitatively assess the diseased lung volume. The radiological data were analyzed by three expert consultant radiologists to reach consensus. A low CT opacity score (≤10) was found in 18 patients (24.7%), while a high CT opacity score (>10) was found in 55 patients (75.3%). Pulmonary embolism was found in 24 patients (32.9%); three of them had low CT opacity scores. Four other indirect vasculopathy CTPA signs were identified: (1) pulmonary vascular enlargement (57 patients—78.1%), (2) pulmonary hypertension (14 patients—19.2%), (3) vascular tree-in-bud pattern (10 patients—13.7%), and (4) pulmonary infarction (three patients—4.1%). There were no significant associations between these signs and the CT opacity score (0.3205–0.7551, all >0.05). Furthermore, both pulmonary vascular enlargement and the vascular tree-in-bud sign were found in patients without pulmonary embolism and low CT-severity scores (13/15–86.7% and 2/15–13.3%, respectively). Conclusion Pulmonary vascular enlargement or, less commonly, vascular tree-in-bud pattern are both indirect vascular angiopathy signs on CTPA that can explain the respiratory deterioration which complicates COVID-19 in the absence of severe parenchymal involvement or acute pulmonary embolism.

Download Full-text

Video teaching of piano playing and singing based on computer artificial intelligence system and virtual image processing

Journal of Ambient Intelligence and Humanized Computing ◽

10.1007/s12652-021-03099-8 ◽

2021 ◽

Author(s):

Bing He

Keyword(s):

Artificial Intelligence ◽

Image Processing ◽

Virtual Image ◽

Artificial Intelligence System ◽

Intelligence System ◽

Piano Playing

Download Full-text

AGASSISTANT: an Artificial Intelligence System for Discovering Patterns in Agricultural Knowledge and Creating Diagnostic Advisory Systems

Agronomy Journal ◽

10.2134/agronj1989.00021962008100020033x ◽

1989 ◽

Vol 81 (2) ◽

pp. 306-312 ◽

Cited By ~ 2

Author(s):

T. W. Fermanian ◽

R. S. Michalski ◽

B. Katz ◽

J. Kelly

Keyword(s):

Artificial Intelligence ◽

Artificial Intelligence System ◽

Intelligence System ◽

Agricultural Knowledge ◽

Advisory Systems

Download Full-text