Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 48,121 to 48,130 of 224,199 articles

Development and validation of a machine learning-based nomogram model integrating LASSO regression and multiple evaluation methods for predicting early sepsis risk in acute abdomen.

European journal of medical research Feb 21, 2026
BACKGROUND: Sepsis secondary to acute abdomen is a critical driver of clinical deterioration and mortality, with outcomes closely linked to sepsis severity and the timeliness of intervention. However, existing single biomarkers or scoring systems exh... read more 

From machine learning to causal insight: a robust 12-gene signature to distinguish sepsis risk from systemic inflammatory response syndrome.

European journal of medical research Feb 21, 2026
BACKGROUND: Sepsis, a life-threatening condition driven by a dysregulated host response, poses significant challenges for early diagnosis and early intervention. This study aimed to identify robust biomarkers capable of distinguishing sepsis from non... read more 

Uncovering biosecurity gaps: risk factors for PRRSV seropositivity in Costa Rican pig farms identified through machine learning.

Porcine health management Feb 21, 2026
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Machine learning-based prediction of persistent diabetic macular edema using OCT-derived structural biomarkers and clinical features.

European journal of medical research Feb 21, 2026
BACKGROUND: Persistent diabetic macular edema (DME) remains a leading cause of vision loss in diabetic retinopathy, even with anti-VEGF therapy. About 30-40% of patients respond poorly after standard loading doses, resulting in prolonged disease and ... read more 

Multicentre development and validation of a risk model integrating immunotherapy and coagulation biomarkers for thrombosis in autoimmune neurological disorders.

International immunopharmacology Feb 21, 2026
PURPOSE: Patients with Autoimmune Neurological Disorders (ANDs) require routine immunomodulatory therapy, which inherently increases thrombosis risk. Despite this recognised association, reliable tools for thrombosis prediction remain limited, highli... read more 

Validity of a novel web application for measuring active range of motion and its reliability as a self-measurement method in telerehabilitation.

International journal of medical informatics Feb 21, 2026
PURPOSE: As a result of the emergence of Artificial Intelligence (AI), new applications for measuring active range of motion (AROM) in telerehabilitation (TR) are being developed. The main objectives of the present study were to evaluate the validity... read more 

External validation of a pre-trained hybrid convolutional neural network in radiographers agreement of positioning in lateral knee radiographs.

Radiography (London, England : 1995) Feb 21, 2026
INTRODUCTION: Accurate positioning in lateral knee radiographs is essential for diagnostic quality but prone to inter-observer variability. Artificial intelligence (AI) may standardize quality assessment, yet its influence on radiographers' critical ... read more 

Multiple screen addiction and neurological complaints in adolescents: A machine learning-based classification model.

Acta psychologica Feb 21, 2026
INTRODUCTION: Multiple screen addiction is a growing public health problem, especially among young people. Early detection and classification of screen addiction are important for the prevention of neurological complaints. OBJECTIVE: The current stud... read more 

Het2Gene: a phenotype-driven model for gene prioritization by heterogeneous graph embedding.

Computers in biology and medicine Feb 21, 2026
Mendelian genetic diseases pose a significant global health burden. Early identification of causative genes is crucial for halting disease progression and developing targeted therapies. However, diagnosing causal genes from next-generation sequencing... read more 

Accuracy of automated 3D biliary tract reconstruction compared to ERCP to assess Bismuth-Corlette classification in patients with perihilar cholangiocarcinoma.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Feb 21, 2026
INTRODUCTION: Accurate descriptions of the extent of disease in intrahepatic bile ducts are essential for managing patients with perihilar cholangiocarcinoma (pCCA). This study describes and assesses a new, automated Computed Tomography (CT)-scan-bas... read more 
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