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Identification of common diagnostic genes and molecular pathways in endometriosis and systemic lupus erythematosus by machine learning approach and in vitro experiment.
International journal of medical sciences
Jan 1, 2025
Growing research suggests that endometriosis and systemic lupus erythematosus (SLE) are both chronic inflammatory diseases and closely related, but no studies have explored their common molecular characteristics and underlying mechanisms. Based on GE...
Development of Time-Aggregated Machine Learning Model for Relapse Prediction in Pediatric Crohn's Disease.
Clinical and translational gastroenterology
Jan 1, 2025
INTRODUCTION: Pediatric Crohn's disease (CD) easily progresses to an active disease compared with adult CD, making it important to predict and minimize CD relapses. However, prediction of relapse at various time points (TPs) during pediatric CD remai...
Enhancing Clinical Decision Making by Predicting Readmission Risk in Patients With Heart Failure Using Machine Learning: Predictive Model Development Study.
JMIR medical informatics
Dec 31, 2024
BACKGROUND: Patients with heart failure frequently face the possibility of rehospitalization following an initial hospital stay, placing a significant burden on both patients and health care systems. Accurate predictive tools are crucial for guiding ...
Machine Learning Prediction of Early Recurrence in Gastric Cancer: A Nationwide Real-World Study.
Annals of surgical oncology
Dec 30, 2024
BACKGROUND: Patients with gastric cancer (GC) who experience early recurrence (ER) within 2 years postoperatively have poor prognoses. This study aimed to analyze and predict ER after curative surgery for patients with GC using machine learning (ML) ...
Machine learning algorithms in constructing prediction models for assisted reproductive technology (ART) related live birth outcomes.
Scientific reports
Dec 30, 2024
Currently applicable models for predicting live birth outcomes in patients who received assisted reproductive technology (ART) have methodological or study design limitations that greatly obstruct their dissemination and application. Models suitable ...
Analysis of diagnostic genes and molecular mechanisms of Crohn's disease and colon cancer based on machine learning algorithms.
Scientific reports
Dec 30, 2024
Crohn's disease (CD) is a chronic inflammatory bowel condition, and colon adenocarcinoma (COAD), as one of the most prevalent malignant tumors of the digestive tract, has been indicated by research to have a close association with CD. This study empl...
Prediction of prognosis in patients with cerebral contusions based on machine learning.
Scientific reports
Dec 30, 2024
Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effective...
Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma.
Scientific reports
Dec 30, 2024
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the...
Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions.
Scientific reports
Dec 28, 2024
This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breas...
Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models.
Scientific reports
Dec 28, 2024
Failure to predict stroke promptly may lead to delayed treatment, causing severe consequences like permanent neurological damage or death. Early detection using deep learning (DL) and machine learning (ML) models can enhance patient outcomes and miti...
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