AIMC Topic: Sex Factors
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Uncovering nonlinear patterns in time-sensitive prehospital breathing emergencies: an exploratory machine learning study.
BMC medical informatics and decision making
Jun 3, 2025
BACKGROUND: Timely prehospital care is crucial for patients presenting with high-risk time-sensitive (HRTS) conditions. However, the interplay between response time and demographic factors in patients with breathing problems remains insufficiently un...
Gasdermin D drives the systemic storm and mortality after trauma with hemorrhage to a greater degree in biological females than males.
Science translational medicine
May 28, 2025
Severe injury accompanied by hemorrhagic shock triggers an early release of cell constituents into the circulation, referred to as the systemic storm. The systemic storm drives the systemic inflammatory response and is associated with increased morta...
Examining the empathy levels of medical students using CHAID analysis.
BMC medical education
May 19, 2025
BACKGROUND: Empathy is a key factor in the medical field as it strengthens doctor-patient relationships, enhances communication, and leads to improved patient outcomes. This study aims to investigate the empathy levels of medical students, providing ...
Gender-specific sarcopenia screening in hemodialysis: insights from lower limb strength and physiological indicators.
BMC nephrology
May 19, 2025
OBJECTIVE: Maintenance hemodialysis (MHD) patients often suffer from sarcopenia, affecting lower limb muscle strength and increasing the risk of falls and mortality. This study aims to develop an auxiliary screening model for sarcopenia in MHD patien...
[Cluster predictors of trajectories of leisure-time physical activity intensity in men and women from ELSA-Brasil].
Cadernos de saude publica
May 19, 2025
The maintenance of physical activity over time is a challenge for public health. Predictors of different physical activity intensities have not been sufficiently analyzed. This study aimed to identify clusters of trajectories of physical activity int...
Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization.
Nature cardiovascular research
May 16, 2025
Large-cohort imaging and diagnostic studies often assess cardiac function but overlook underlying biological mechanisms. Cardiac digital twins (CDTs) are personalized physics-constrained and physiology-constrained in silico representations, uncoverin...
GLIO-Select: Machine Learning-Based Feature Selection and Weighting of Tissue and Serum Proteomic and Metabolomic Data Uncovers Sex Differences in Glioblastoma.
International journal of molecular sciences
May 2, 2025
Glioblastoma (GBM) is a fatal brain cancer known for its rapid and aggressive growth, with some studies indicating that females may have better survival outcomes compared to males. While sex differences in GBM have been observed, the underlying biolo...
Gender Authorship Among Urology Artificial Intelligence Publications: A 10-Year Retrospective Analysis.
Urology
Apr 30, 2025
We aim to characterize gender authorship in urology-related artificial intelligence (AI) research. A retrospective review was performed using MEDLINE, Embase, and Web of Science (Clarivate) databases (2014-2024). First and senior author gender was es...
Optimising coronary imaging decisions with machine learning: an external validation study.
Open heart
Apr 24, 2025
BACKGROUND: Exclusion of coronary stenosis in individuals with suggestive symptoms is challenging. Cardiac CT or coronary angiography is often used but is inefficient and costly and involves risks. Sex-stratified algorithms based on electronic health...
Middle Aged
Electronic Health Records
Netherlands
Predictive Value of Tests
Humans
Sex Factors
Female
Coronary Angiography
Machine Learning
Coronary Vessels
Reproducibility of Results
Coronary Artery Disease
Algorithms
Computed Tomography Angiography
Aged
Retrospective Studies
Coronary Stenosis
Male
Exploring the influence of artificial intelligence integration on personalized learning: a cross-sectional study of undergraduate medical students in the United Kingdom.
BMC medical education
Apr 17, 2025
BACKGROUND: With the integration of Artificial Intelligence (AI) into educational systems, its potential to revolutionize learning, particularly in content personalization and assessment support, is significant. Personalized learning, supported by AI...
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