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Prediction of late-onset depression in the elderly Korean population using machine learning algorithms.

Scientific reports
Late-onset depression (LOD) refers to depression that newly appears in elderly individuals without prior depression episodes. Predicting future depression is crucial for mitigating the risk of major depression in prospective patients. This study aims...

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...

Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning.

Scientific reports
With the growing global challenge of drug abuse, there is an urgent need for rapid, accurate, and cost-effective drug detection methods. This study introduces an innovative approach to drug abuse screening by quickly detecting ephedrine (EPH) in tear...

Bias Mitigation in Primary Health Care Artificial Intelligence Models: Scoping Review.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) predictive models in primary health care have the potential to enhance population health by rapidly and accurately identifying individuals who should receive care and health services. However, these models als...

The Willingness of Doctors to Adopt Artificial Intelligence-Driven Clinical Decision Support Systems at Different Hospitals in China: Fuzzy Set Qualitative Comparative Analysis of Survey Data.

Journal of medical Internet research
BACKGROUND: Artificial intelligence-driven clinical decision support systems (AI-CDSSs) are pivotal tools for doctors to improve diagnostic and treatment processes, as well as improve the efficiency and quality of health care services. However, not a...

Liver fibrosis stage classification in stacked microvascular images based on deep learning.

BMC medical imaging
BACKGROUND: Monitoring fibrosis in patients with chronic liver disease (CLD) is an important management strategy. We have already reported a novel stacked microvascular imaging (SMVI) technique and an examiner scoring evaluation method to improve fib...

Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era.

PloS one
Although prediction models for heart transplantation outcomes have been developed previously, a comprehensive benchmarking of survival machine learning methods for mortality prognosis in the most contemporary era of heart transplants following the 20...

An interpretable machine learning model for predicting in-hospital mortality in ICU patients with ventilator-associated pneumonia.

PloS one
BACKGROUND: Ventilator-associated pneumonia (VAP) is a common nosocomial infection in ICU, significantly associated with poor outcomes. However, there is currently a lack of reliable and interpretable tools for assessing the risk of in-hospital morta...