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Identification of right ventricular dysfunction with LogNNet based diagnostic model: A comparative study with supervised ML algorithms.
Scientific reports
Jul 12, 2025
Right ventricular dysfunction (RVD) is strongly associated with increased mortality in patients with acute pulmonary embolism (PE), making its early detection crucial. Identifying RVD risk factors rapidly, accurately, and economically within the acut...
Integrated clinicopathological-radiomic-blood model for glioma survival prediction via machine learning: a multicenter cohort study.
Neurosurgical review
Jul 12, 2025
BACKGROUND: Glioma is characterized by a poor prognosis and limited possibilities for treatment. Previous studies have developed prediction models for glioma using genetic, clinical, pathological, imaging and other aspects; however, few studies have ...
Machine learning-based prediction of stone-free rate after retrograde intrarenal surgery for lower pole renal stones.
World journal of urology
Jul 12, 2025
BACKGROUND: Lower pole renal stones (LPS) present unique challenges for retrograde intrarenal surgery (RIRS) due to unfavorable anatomical features, often resulting in suboptimal stone-free rates (SFR). Recent advancements in machine learning (ML) of...
Cost-effectiveness analysis of artificial intelligence (AI) in earlier detection of liver lesions in cirrhotic patients at risk of hepatocellular carcinoma in Italy.
Journal of medical economics
Jul 11, 2025
BACKGROUND: Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third most common cause of cancer-related death. Cirrhosis is a major contributing factor, accounting for over 90% of HCC cases. With the high mortality rate...
Letter to the Editor: Robustness of osteoporosis risk prediction models with enhanced statistical analyses.
Computers in biology and medicine
Jul 11, 2025
In response to Oka et al.'s letter, we conducted additional statistical analyses to validate the robustness of our osteoporosis risk prediction model using NHANES 2007-2014 data (n = 7924). We evaluated 10 key predictors through Spearman's rho, Kenda...
Hierarchical deep learning system for orbital fracture detection and trap-door classification on CT images.
Computers in biology and medicine
Jul 11, 2025
OBJECTIVE: To develop and evaluate a hierarchical deep learning system that detects orbital fractures on computed tomography (CT) images and classifies them as depressed or trap-door types.
Enhancing Parkinson's disease prediction using meta-heuristic optimized machine learning models.
Personalized medicine
Jul 11, 2025
Parkinson's disease is a progressive neurological disorder affecting movement and cognition. Early detection is crucial but challenging with traditional methods. This study applies meta-heuristic optimization to enhance machine learning prediction mo...
Prediction of Percutaneous Coronary Intervention Success in Patients With Moderate to Severe Coronary Artery Calcification Using Machine Learning Based on Coronary Angiography: Prospective Cohort Study.
Journal of medical Internet research
Jul 11, 2025
BACKGROUND: Given the challenges faced during percutaneous coronary intervention (PCI) for heavily calcified lesions, accurately predicting PCI success is crucial for enhancing patient outcomes and optimizing procedural strategies.
Size-Specific Predictors for Malignancy Risk in Follicular Thyroid Neoplasms: Machine Learning Analysis.
JMIR cancer
Jul 11, 2025
BACKGROUND: Surgeons often face challenges in distinguishing between benign and malignant follicular thyroid neoplasms (FTNs), particularly small tumors, until diagnostic surgery is performed.
Non-invasive identification of TKI-resistant NSCLC: a multi-model AI approach for predicting EGFR/TP53 co-mutations.
BMC pulmonary medicine
Jul 10, 2025
OBJECTIVES: To investigate the value of multi-model based on preoperative CT scans in predicting EGFR/TP53 co-mutation status.
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