ArticleCureus2024
Deep Machine Learning Might Aid in Combating Intensive Care Unit-Acquired Weakness.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Assessment of Pain Intensity Using Deep Learning Models in Non-Communicative Intensive Care Patients.Nursing in critical care · 2026Article
- Risk Factors and Prediction Model for ICU-Acquired Weakness in Severe Acute Pancreatitis: A Retrospective Cohort Study.Journal of inflammation research · 2026Article
- Integrating sarcopenia into ICU-acquired weakness risk stratification: a machine learning-based prediction model for critical care.Frontiers in nutrition · 2026Article
- Mapping Artificial Intelligence Research Trends in Critical Care Nursing: A Bibliometric Analysis.Journal of multidisciplinary healthcare · 2025Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.