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Association and prediction of serum lipid profiles with incident stroke in the CHARLS cohort: A machine learning analysis.

Medicine
Using the 2011 baseline data of the China health and retirement longitudinal study, we examined the associations between serum lipids and other risk factors and incident stroke, and developed and compared multiple machine learning models for stroke-r...

Orthopedic perioperative nursing under navigation nurse management: Machine learning-based risk prediction models for postoperative recovery quality and explainable artificial intelligence analysis.

Medicine
This study aimed to evaluate the effectiveness of navigation nurse management (NNM) in orthopedic perioperative care and develop machine learning (ML) models to predict postoperative recovery quality. We sought to identify key factors influencing rec...

The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) as predictors of hypertensive patients: Analyses of NHANES data with machine learning.

Medicine
Elevated values of the non-HDL/HDL cholesterol ratio (NHHR) have been associated with increased hypertension risk, indicating its potential as a pathogenic factor, but its assessment remains challenging. We analyzed data from 22,562 hypertensive part...

Machine learning-based screening of characteristic factors for urinary tract infection following ureteral stone surgery and construction and validation of risk prediction models.

Medicine
Ureteroscopic lithotripsy has emerged as the cornerstone treatment modality for ureteral stones due to its exceptional success rates and minimal complication profiles. Nevertheless, postoperative urinary tract infection (UTI) remains a prevalent and ...

Modeling Early-Onset Cancer Kinetics Reveals Changes in Underlying Risk and the Impact of Population Screening.

Cancer research
UNLABELLED: Recent studies have reported increases in early-onset cancer cases (diagnosed less than 50 years of age) and raised questions about whether the increase is related to earlier diagnosis from nonspecific medical tests as reflected by decrea...

Multimodal Approach Predicts Relapse upon Cessation of Immune Checkpoint Inhibitors in Advanced Melanoma.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Treatment with immune checkpoint inhibitors (ICI) in advanced melanoma can result in durable responses, yet an algorithm to decide which patients can safely discontinue ICI is still lacking.

Identifying azithromycin responders with an individual treatment effect model in COPD.

Thorax
OBJECTIVE: Long-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease (COPD). However, patients would benefit from better identification of responders and non-responders to minimise unnecessary ...

Exploring the impact of generative AI tools on healthcare delivery in Tanzania.

Journal of health organization and management
PURPOSE: This study explores the impact of generative AI tools on healthcare delivery in Tanzania. It examines its potential to enhance efficiency, accessibility and decision-making in health informatics while addressing infrastructure, ethics and eq...

Artificial intelligence and employee performance in Uganda's healthcare institutions: exploring the mediation effects of perceived ease of use and skills enhancement.

Journal of health organization and management
PURPOSE: The purpose of this study is to investigate the relationship between artificial intelligence (AI) and employee performance in Uganda's healthcare institutions, with a specific focus on exploring the mediating effects of perceived ease of use...

Detection of common bile duct dilatation on magnetic resonance cholangiopancreatography by deep learning.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: This study aims to detect common bile duct (CBD) dilatation using deep learning methods from artificial intelligence algorithms.