AIMC Topic: Cohort Studies
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Repeatability of AI-based, automatic measurement of vertebral and cardiovascular imaging biomarkers in low-dose chest CT: the ImaLife cohort.
European radiology
Jan 8, 2025
OBJECTIVE: To evaluate the repeatability of AI-based automatic measurement of vertebral and cardiovascular markers on low-dose chest CT.
Early identification of potentially reversible cancer cachexia using explainable machine learning driven by body weight dynamics: a multicenter cohort study.
The American journal of clinical nutrition
Jan 8, 2025
BACKGROUND: Cachexia is associated with multiple adverse outcomes in cancer. However, clinical decision-making for oncology patients at the cachexia stage presents significant challenges.
Blood metal levels predict digestive tract cancer risk using machine learning in a U.S. cohort.
Scientific reports
Jan 8, 2025
BACKGROUND: Environmental metal exposure has been implicated in the development of digestive tract cancers, although the specific associations remain poorly defined. This study aimed to investigate the relationship between blood metal levels and the ...
Predicting cardiovascular disease in patients with mental illness using machine learning.
European psychiatry : the journal of the Association of European Psychiatrists
Jan 8, 2025
BACKGROUND: Cardiovascular disease (CVD) is twice as prevalent among individuals with mental illness compared to the general population. Prevention strategies exist but require accurate risk prediction. This study aimed to develop and validate a mach...
Multi‑omics identification of a novel signature for serous ovarian carcinoma in the context of 3P medicine and based on twelve programmed cell death patterns: a multi-cohort machine learning study.
Molecular medicine (Cambridge, Mass.)
Jan 8, 2025
BACKGROUND: Predictive, preventive, and personalized medicine (PPPM/3PM) is a strategy aimed at improving the prognosis of cancer, and programmed cell death (PCD) is increasingly recognized as a potential target in cancer therapy and prognosis. Howev...
External validation of an artificial intelligence model using clinical variables, including ICD-10 codes, for predicting in-hospital mortality among trauma patients: a multicenter retrospective cohort study.
Scientific reports
Jan 7, 2025
Artificial intelligence (AI) is being increasingly applied in healthcare to improve patient care and clinical outcomes. We previously developed an AI model using ICD-10 (International Classification of Diseases, Tenth Revision) codes with other clini...
Deep learning-based prediction of HER2 status and trastuzumab treatment efficacy of gastric adenocarcinoma based on morphological features.
Journal of translational medicine
Jan 6, 2025
BACKGROUND: First-line treatment for advanced gastric adenocarcinoma (GAC) with human epidermal growth factor receptor 2 (HER2) is trastuzumab combined with chemotherapy. In clinical practice, HER2 positivity is identified through immunohistochemistr...
Finding Predictive Factors of Stabilization Exercise Adherence in Randomized Controlled Trials on Low Back Pain: An Individual Data Reanalysis Using Machine Learning Techniques.
Archives of physical medicine and rehabilitation
Jan 3, 2025
OBJECTIVE: To identify predictors of adherence in supervised and self-administered exercise interventions for individuals with low back pain.
Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.
Pharmacotherapy
Jan 3, 2025
BACKGROUND: Fluid overload (FO) in the intensive care unit (ICU) is common, serious, and may be preventable. Intravenous medications (including administered volume) are a primary cause for FO but are challenging to evaluate as a FO predictor given th...
Differential gray matter correlates and machine learning prediction of abuse and internalizing psychopathology in adolescent females.
Scientific reports
Jan 3, 2025
Childhood abuse represents one of the most potent risk factors for the development of psychopathology during childhood, accounting for 30-60% of the risk for onset. While previous studies have separately associated reductions in gray matter volume (G...
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