AIMC Topic: Female

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A catalyst for education? A study on the impact of artificial intelligence assisted learning in painting courses on college students' continuous learning intention.

Acta psychologica
This study examines artificial intelligence in college students' painting education and their potential impact on students' continuous learning intention. In this study, two surveys were conducted. The first survey included 793 valid samples, and the...

Does restrictive anorexia nervosa impact brain aging? A machine learning approach to estimate age based on brain structure.

Computers in biology and medicine
Anorexia nervosa (AN), a severe eating disorder marked by extreme weight loss and malnutrition, leads to significant alterations in brain structure. This study used machine learning (ML) to estimate brain age from structural MRI scans and investigate...

Automated three-dimensional body composition analysis identifies visceral adipose tissue radiodensity as a predictor of mortality and recurrence in colorectal cancer.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND: Artificial intelligence enables automated three-dimensional (3D) volumetric body composition (BC) analysis from computed tomography (CT), opposed to single third lumbar vertebra (L3) slices alone. This study aimed to identify relationship...

Integrative exome sequencing and machine learning identify MICB and interferon pathway genes as contributors to SSc risk.

Annals of the rheumatic diseases
OBJECTIVES: Systemic sclerosis (SSc) is a complex autoimmune disease with both known and unidentified genetic contributors. While genome-wide association studies (GWAS) have implicated multiple loci, many reside in noncoding regions. We aimed to iden...

Predicting time to live birth with deep learning embryo ranking: a novel multiple imputation approach.

Human reproduction (Oxford, England)
STUDY QUESTION: What is the clinical utility of embryo selection algorithms in estimating the time to live birth (TTLB)?

Multimodal deep learning for enhanced breast cancer diagnosis on sonography.

Computers in biology and medicine
This study introduces a novel multimodal deep learning model tailored for the differentiation of benign and malignant breast masses using dual-view breast ultrasound images (radial and anti-radial views) in conjunction with corresponding radiology re...

Association between metal mixture in urine and abnormal blood pressure and mediated effect of oxidative stress based on BKMR and Machine learning method.

Ecotoxicology and environmental safety
BACKGROUND: Exposure to heavy metals represents a significant risk factor for hypertension and blood pressure disorders. Notably, current evidence indicates that the key biological processes of oxidative stress, inflammation, and endothelial dysfunct...

Sepsis criteria and kidney function: eliminating sex, age and economic status biases.

Nature reviews. Nephrology
The kidney is a target organ for the dysregulated host response to infection that defines sepsis, and acute kidney injury (AKI) is often an early manifestation of this response. Current sepsis criteria for adults (Sepsis-3) continue to include outmod...

Interpretable Machine Learning Prediction Model for Predicting Mortality Risk of ICU Patients With Pressure Ulcers Based on the Braden Scale: A Clinical Study Based on MIMIC-IV.

Journal of clinical nursing
AIMS: This study was to create an interpretable machine learning model to predict the risk of mortality within 90 days for ICU patients suffering from pressure ulcers.

Clinical phenotypes and risk of early hemodynamic deterioration in intermediate-high-risk patients with acute pulmonary embolism.

Thrombosis research
INTRODUCTION: Intermediate-high-risk pulmonary embolism (PE) patients face elevated risks of sudden clinical deterioration in early hours after symptoms onset. We performed a hierarchical cluster analysis among intermediate-high risk PE patients to i...