AIMC Topic: Cohort Studies

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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
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...

Development and Validation of a Model Based on Circulating Biomarkers for Discriminating Symptomatic Spontaneous Intracranial Artery Dissection.

Translational stroke research
Spontaneous intracranial artery dissection (sIAD) is the leading cause of stroke in young individuals. Identifying high-risk sIAD cases that exhibit symptoms and are likely to progress is crucial for treatment decision-making. This study aimed to dev...

Deep learning-based prediction of HER2 status and trastuzumab treatment efficacy of gastric adenocarcinoma based on morphological features.

Journal of translational medicine
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...

Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.

Pharmacotherapy
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
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...

Gut microbial composition associated with risk of premature aging in women with Yin-deficiency constitution.

Frontiers in cellular and infection microbiology
BACKGROUND: Yin-deficiency constitution (YinDC) refers to a traditional Chinese medicine concept, characterized by an imbalance state that includes an imbalance in the gut microbiota, resulting from a relative deficiency of Yin fluids within the body...

Predicting host health status through an integrated machine learning framework: insights from healthy gut microbiome aging trajectory.

Scientific reports
The gut microbiome, recognized as a critical component in the development of chronic diseases and aging processes, constitutes a promising approach for predicting host health status. Previous research has underscored the potential of microbiome-based...

SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI.

Scientific reports
Cerebral microbleeds (CMB) represent a feature of cerebral small vessel disease (cSVD), a prominent vascular contributor to age-related cognitive decline, dementia, and stroke. They are visible as spherical hypointense signals on T2*- or susceptibili...