| Literature DB >> 33733232 |
Jay Carriere1, Hareem Shafi1, Katelyn Brehon2, Kiran Pohar Manhas3, Katie Churchill4,5, Chester Ho3,6, Mahdi Tavakoli1.
Abstract
The COVID-19 pandemic has profoundly affected healthcare systems and healthcare delivery worldwide. Policy makers are utilizing social distancing and isolation policies to reduce the risk of transmission and spread of COVID-19, while the research, development, and testing of antiviral treatments and vaccines are ongoing. As part of these isolation policies, in-person healthcare delivery has been reduced, or eliminated, to avoid the risk of COVID-19 infection in high-risk and vulnerable populations, particularly those with comorbidities. Clinicians, occupational therapists, and physiotherapists have traditionally relied on in-person diagnosis and treatment of acute and chronic musculoskeletal (MSK) and neurological conditions and illnesses. The assessment and rehabilitation of persons with acute and chronic conditions has, therefore, been particularly impacted during the pandemic. This article presents a perspective on how Artificial Intelligence and Machine Learning (AI/ML) technologies, such as Natural Language Processing (NLP), can be used to assist with assessment and rehabilitation for acute and chronic conditions.Entities:
Keywords: COVID-19; artificial intelligence; natural language processing; neuromusculoskeletal rehabilitation; smart health
Year: 2021 PMID: 33733232 PMCID: PMC7907599 DOI: 10.3389/frai.2021.613637
Source DB: PubMed Journal: Front Artif Intell ISSN: 2624-8212