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Identification of Risk Group for Root Caries and Analysis of Associated Factors in Older Adults Using Unsupervised Machine Learning Clustering.

Clinical interventions in aging 40297169
PURPOSE: This study aimed to identify the high-risk group for root caries using unsupervised machine learning and to explore the associated factors.
Age Factors Aged Cluster Analysis Cross-Sectional Studies Female Humans Logistic Models Male Risk Assessment Risk Factors ROC Curve Root Caries Unsupervised Machine Learning
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Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus.

Nutrients 40289953
: Diet plays an important role in preventing and managing the progression from prediabetes to type 2 diabetes mellitus (T2DM). This study aims to develop prediction models incorporating specific dietary indicators and explore the performance in T2DM ...
Adult Aged China Diabetes Mellitus, Type 2 Diet Disease Progression Female Humans Machine Learning Male Middle Aged Prediabetic State Retrospective Studies ROC Curve
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Development and validation a radiomics combined clinical model predicts treatment response for esophageal squamous cell carcinoma patients.

BMC gastroenterology 40301780
PURPOSE: This study is aimed to develop and validate a machine learning model, which combined radiomics and clinical characteristics to predicting the definitive chemoradiotherapy (dCRT) treatment response in esophageal squamous cell carcinoma (ESCC)...
Aged Chemoradiotherapy Esophageal Neoplasms Esophageal Squamous Cell Carcinoma Female Humans Logistic Models Machine Learning Male Middle Aged Nomograms Radiomics Retrospective Studies ROC Curve Tomography, X-Ray Computed Treatment Outcome
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Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis.

BMJ open 40288805
OBJECTIVE: In-hospital cardiac arrest (IHCA) presents a critical challenge with low survival rates and limited prediction tools. Despite advances in resuscitation, predicting 30-day survival remains difficult, and current methods lack interpretabilit...
Aged Aged, 80 and over Cardiopulmonary Resuscitation Cohort Studies Female Heart Arrest Humans Machine Learning Male Middle Aged Registries ROC Curve Survival Rate Sweden
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Identification of Novel Diagnostic Markers for Atherosclerosis Using Machine-Learning Algorithms.

Journal of the College of Physicians and Surgeons--Pakistan : JCPSP 40325572
OBJECTIVE: To outline immune-cell infiltration and identify diagnostic genes for atherosclerosis (AS) to better understand the potential molecular processes involved in AS development.
Algorithms Atherosclerosis Biomarkers China Gene Expression Profiling Humans Inflammation Machine Learning ROC Curve
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Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births.

BMC pregnancy and childbirth 40319253
OBJECTIVE: This study aimed to develop a machine learning (ML) model integrated with SHapley Additive exPlanations (SHAP) analysis to predict postpartum hemorrhage (PPH) following vaginal deliveries, offering a potential tool for personalized risk as...
Adult Area Under Curve China Delivery, Obstetric Female Humans Machine Learning Postpartum Hemorrhage Predictive Value of Tests Pregnancy Retrospective Studies Risk Assessment ROC Curve
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Deep learning model for predicting the RAS oncogene status in colorectal cancer liver metastases.

Journal of cancer research and therapeutics 40317140
BACKGROUND: To develop a deep learning radiomics (DLR) model based on contrast-enhanced computed tomography (CECT) to assess the rat sarcoma (RAS) oncogene status and predict targeted therapy response in colorectal cancer liver metastases (CRLM).
Adult Aged Biomarkers, Tumor Colorectal Neoplasms Deep Learning Female Genes, ras Humans Liver Neoplasms Male Middle Aged Mutation Prognosis Retrospective Studies ROC Curve Tomography, X-Ray Computed
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Interpretable machine learning model for predicting post-hepatectomy liver failure in hepatocellular carcinoma.

Scientific reports 40316613
Post-hepatectomy liver failure (PHLF) is a severe complication following liver surgery. We aimed to develop a novel, interpretable machine learning (ML) model to predict PHLF. We enrolled 312 hepatocellular carcinoma (HCC) patients who underwent hepa...
Adult Aged Algorithms Carcinoma, Hepatocellular Female Hepatectomy Humans Liver Failure Liver Neoplasms Machine Learning Male Middle Aged Postoperative Complications Prospective Studies ROC Curve
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Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy.

Scientific reports 40312440
Anoikis and immune cell infiltration are pivotal factors in the pathophysiological mechanism of diabetic nephropathy (DN), yet a comprehensive understanding of the mechanism is lacking. This work aimed to pinpoint distinctive anoikis-related genes (A...
Algorithms Anoikis Computational Biology Databases, Genetic Diabetic Nephropathies Gene Expression Profiling Gene Expression Regulation Gene Ontology Gene Regulatory Networks Humans Machine Learning ROC Curve
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Selection of neuroendocrine markers in diagnostic workup of neuroendocrine neoplasms: The real-world data and machine learning model algorithms.

Cancer cytopathology 40289395
BACKGROUND: Accurate diagnosis of neuroendocrine neoplasms (NENs) is challenging, especially in poorly differentiated neuroendocrine carcinomas (NECs). This study was aimed to search the best or best combination of neuroendocrine markers in the diagn...
Adult Aged Algorithms Biomarkers, Tumor Carcinoma, Neuroendocrine CD56 Antigen Chromogranins Female Humans Machine Learning Male Middle Aged Neural Networks, Computer Neuroendocrine Tumors Repressor Proteins ROC Curve Sensitivity and Specificity Synaptophysin
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