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Unlocking the Complexity of Co-Occurring Chronic Pain and Psychological Distress in Young Adults: Insights from Machine Learning and Explainable AI
Posted innews Psychiatry Public Health

Unlocking the Complexity of Co-Occurring Chronic Pain and Psychological Distress in Young Adults: Insights from Machine Learning and Explainable AI

Posted by By MedXY 10/24/2025
This study applies machine learning and explainable AI to identify factors associated with chronic pain, psychological distress, and their co-occurrence in Norwegian young adults, highlighting the importance of integrated approaches for early intervention.
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Advancing Early Pediatric Sepsis Detection: Machine Learning Models Predicting Onset Within 48 Hours
Posted inAI Critical Care Emergency Medicine Pediatrics Specialties

Advancing Early Pediatric Sepsis Detection: Machine Learning Models Predicting Onset Within 48 Hours

Posted by By MedXY 10/21/2025
This study developed and validated machine learning models with high accuracy to predict early pediatric sepsis and septic shock within 48 hours using multisite electronic health record data in emergency departments.
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Advancing Precision Medicine in Hepatocellular Carcinoma: Machine Learning Radiomic Models Surpass Clinical Biomarkers in Predicting Immunotherapy Outcomes
Posted inAI news Oncology Radiology Specialties

Advancing Precision Medicine in Hepatocellular Carcinoma: Machine Learning Radiomic Models Surpass Clinical Biomarkers in Predicting Immunotherapy Outcomes

Posted by By MedXY 09/27/2025
Integrated radiomic-clinical machine learning models outperform traditional clinical biomarkers in predicting survival and treatment response in unresectable hepatocellular carcinoma patients undergoing atezolizumab plus bevacizumab therapy.
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Optimizing Treatment Selection for Hepatocellular Carcinoma: Machine Learning Guidance in Choosing Liver Transplantation versus Surgical Resection
Posted inGeneral Surgery news Oncology Specialties

Optimizing Treatment Selection for Hepatocellular Carcinoma: Machine Learning Guidance in Choosing Liver Transplantation versus Surgical Resection

Posted by By MedXY 09/23/2025
A machine learning model accurately stratifies patients with hepatocellular carcinoma to guide individualized selection between liver transplantation and surgical resection, improving survival outcomes while addressing donor scarcity and patient heterogeneity.
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Harnessing Machine Learning to Predict High-Risk Coronary Artery Disease: Insights from the SCOT-HEART Trial
Posted inAI Cardiology Specialties

Harnessing Machine Learning to Predict High-Risk Coronary Artery Disease: Insights from the SCOT-HEART Trial

Posted by By MedXY 09/14/2025
Machine learning models trained on clinical data improve prediction of coronary artery disease on CT scans compared to traditional risk scores, potentially guiding better resource utilization in cardiovascular care.
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Revolutionizing Early Detection of Pancreatic Cancer: A cfDNA Fragmentomics and Machine Learning Model
Posted inClinical Updates news Oncology Pathology & Lab Medicine

Revolutionizing Early Detection of Pancreatic Cancer: A cfDNA Fragmentomics and Machine Learning Model

Posted by By MedXY 09/08/2025
A new cell-free DNA fragmentomics model combined with machine learning achieves high accuracy for early pancreatic cancer detection, potentially improving patient outcomes through timely intervention.
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Advancing Acute Coronary Syndrome Care: ECG-Based Machine Learning Enhances Risk Stratification
Posted inAI Cardiology Specialties

Advancing Acute Coronary Syndrome Care: ECG-Based Machine Learning Enhances Risk Stratification

Posted by By MedXY 08/16/2025
A prospective study shows that machine learning models trained on 12-lead ECG features outperform HEART score in predicting mortality among chest pain patients, improving risk-based care precision.
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Explainable Artificial Intelligence for Predicting Refractory Ulcerative Colitis: Insights from a Japanese Nationwide Registry
Posted inAI Clinical Updates Gastroenterology news Specialties

Explainable Artificial Intelligence for Predicting Refractory Ulcerative Colitis: Insights from a Japanese Nationwide Registry

Posted by By MedXY 08/07/2025
A machine learning model using nationwide registry data accurately predicts long-term remission in refractory ulcerative colitis and identifies key prognostic factors such as pseudopolyps.
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  • Frailty as a Predictor of Surgical Outcomes in Cricopharyngeus Muscle Dysfunction: Enhancing Patient Selection and Expectations
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  • Environmental Burden and Its Influence on Surgical Outcomes: Unveiling the Hidden Disparities
  • Advancing Surgical Quality Assessment in Distal Gastrectomy: Automated Evaluation of the Critical View of Quality Using Computer Vision
  • Neurotensin Receptor 1: A Key Driver of Immune Exclusion and Poor Prognosis in Colorectal Cancer
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