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Machine learning-based predictive modeling of angina pectoris in an elderly community-dwelling population: Results from the PoCOsteo study.
PloS one
Aug 5, 2025
BACKGROUND: Angina pectoris, a comparatively common complaint among older adults, is a critical warning sign of underlying coronary heart disease. We aimed to develop machine learning-based models using multiple algorithms to predict and identify the...
Natural language processing for kidney ultrasound analysis: correlating imaging reports with chronic kidney disease diagnosis.
Renal failure
Aug 4, 2025
INTRODUCTION: Natural language processing (NLP) has been used to analyze unstructured imaging report data, yet its application in identifying chronic kidney disease (CKD) features from kidney ultrasound reports remains unexplored.
Personalized colorectal cancer risk assessment through explainable AI and Gut microbiome profiling.
Gut microbes
Aug 4, 2025
The clinical adenoma - carcinoma progression represents a well-established framework for understanding colorectal cancer (CRC) development, although the molecular mechanisms underlying this transition remain only partially understood. Increasing evid...
Comparison of machine learning algorithms for predicting length of stay in chronic kidney disease patients.
Computers in biology and medicine
Aug 4, 2025
The length of stay (LOS) for patients in hospitals is crucial for workforce planning, resource allocation, and bed capacity management, impacting healthcare costs, future needs and financial planning. This study focuses on calculating the LOS for Chr...
Vessel-specific reliability of artificial intelligence-based coronary artery calcium scoring on non-ECG-gated chest CT: a comparative study with ECG-gated cardiac CT.
Clinical imaging
Aug 4, 2025
PURPOSE: To evaluate the performance of artificial intelligence (AI)-based coronary artery calcium scoring (CACS) on non-electrocardiogram (ECG)-gated chest CT, using manual quantification as the reference standard, while characterizing per-vessel re...
The relationship between clinical subtypes, prognosis, and treatment in ICU patients with acute cholangitis using unsupervised machine learning methods.
BMC infectious diseases
Aug 4, 2025
BACKGROUND: Acute cholangitis (AC) presents with significant clinical heterogeneity, and existing severity classifications have limited prognostic value in critically ill patients. Subtypes of AC in critically ill patients have not been investigated.
Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas.
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 4, 2025
PURPOSE: Accurate preoperative grading of gliomas is critical for therapeutic planning and prognostic evaluation. We developed a noninvasive machine learning model leveraging whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) b...
Machine learning algorithms for risk factor selection with application to 60-day sepsis morbidity risk for a geriatric hip fracture cohort.
BMC geriatrics
Aug 4, 2025
BACKGROUND: Sepsis after hip fracture in elderly people is a risk factor for mortality. The purpose of this study was to screen for risk factors for 60-day sepsis morbidity after hip fracture and to establish a predictive model using various machine ...
Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization.
Scientific reports
Aug 4, 2025
Falling poses a significant health risk to the elderly, often resulting in severe injuries if not promptly addressed. As the global population increases, the frequency of falls increases along with the associated financial burden. Hence, early detect...
Unsupervised machine learning approach to interpret complex lower urinary tract symptoms and their impact on quality of life in adult women.
World journal of urology
Aug 4, 2025
PURPOSE: To identify clinically meaningful clusters of lower urinary tract symptoms (LUTS) in adult women using an unsupervised machine learning approach and to examine their associations with patient-centered outcomes, including quality of life (QoL...
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