Panda CK, Karim HMR. Deep Machine Learning Might Aid in Combating Intensive Care Unit-Acquired Weakness.
Cureus 2024;
16:e58963. [PMID:
38800279 PMCID:
PMC11126887 DOI:
10.7759/cureus.58963]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/24/2024] [Indexed: 05/29/2024] Open
Abstract
Secondary muscle weakness in critically ill patients like intensive care unit (ICU)-associated weakness is frequently noted in patients with prolonged mechanical ventilation and ICU stay. It can be a result of critical illness, myopathy, or neuropathy. Although ICU-acquired weakness (ICU-AW) has been known for a while, there is still no effective treatment for it. Therefore, prevention of ICU-AW becomes the utmost priority, and knowing the risk factors is crucial. Nevertheless, the pathophysiology and the attributing causes are complex for ICU-AW, and proper delineation and formulation of a preventive strategy from such vast, multifaceted data are challenging. Artificial intelligence has recently helped healthcare professionals understand and analyze such intricate data through deep machine learning. Hence, using such a strategy also helps in knowing the risk factors and their weight as contributors, applying them in formulating a preventive path for ICU-AW worth trials.
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