Artificial Intelligence Medical Compendium

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

Showing 14,151 to 14,160 of 211,815 articles

A Prediction Model for Cardiovascular Death in Individuals with Prediabetes.

Studies in health technology and informatics May 21, 2026
We developed a machine learning model to estimate the personalized risk of cardiovascular (CV) death within 5-years among obese/overweight people with prediabetes. The model has the potential to enhance early preventive CV strategies. read more 

Deep Learning-Based Prediction of Pathogenicity for ABL1 Protein Variants Using Sequence Representation.

Studies in health technology and informatics May 21, 2026
The ABL1 gene encodes a non-receptor tyrosine kinase implicated in leukemia and other genetic disorders. This study presents a deep learning-based approach for predicting the pathogenicity of ABL1 single amino acid variants (SAVs) using amino acid se... read more 

Predicting Pediatric Mortality Across Five Intensive Care Units: Toward an Early Warning Using Machine Learning.

Studies in health technology and informatics May 21, 2026
Despite the advances in critical care and innovations of medical technology, earlier identification of children at high mortality risk remains challenging, particularly across heterogeneous pediatric intensive care unit (ICU) settings. In this study,... read more 

Generalization of ML Models Between ECG and VCG Representation.

Studies in health technology and informatics May 21, 2026
Integrating heterogeneous data sources is vital for developing and validating robust medical machine learning models. Although the 12-lead format is standard in clinical electrocardiography (ECG), many datasets include only single-lead or vectorcardi... read more 

Assessing AI-Based Decision Support in Early Sepsis and AKI Recognition.

Studies in health technology and informatics May 21, 2026
Sepsis and acute kidney injury (AKI) remain among the most critical conditions in acute care, associated with high morbidity and mortality. Early risk recognition is essential but often hampered by nonspecific symptoms. Recent studies have demonstrat... read more 

Grading Shoulder Osteoarthritis in X-ray Images Using Deep Learning Techniques.

Studies in health technology and informatics May 21, 2026
This study attempts to develop a deep learning (DL) model to grade Glenohumeral OA (GHOA) in shoulder x-ray images based on the Hamada classification system. Using a novel image enhancing technique, the final model achieved AUROC scores ranging from ... read more 

DeepSeek R1 Distilled Fails to Perform Well Against the USMLE and Other LLMs with and Without Semantics.

Studies in health technology and informatics May 21, 2026
DeepSeek-R1 Distilled Large Language model (LLM) was touted to be almost as good and much cheeper to generate than traditional LLMs. We compared its ability to answer medical questions from the United States Medical Licensing Examinations (USMLE) and... read more 

OPTIMA-DAW: Improving Cerebral Vasospasm Detection After Aneurysmal Subarachnoid Haemorrhage Using Machine Learning.

Studies in health technology and informatics May 21, 2026
Cerebral vasospasm is a serious complication after aneurysmal subarachnoid haemorrhage (aSAH). We trained machine learning models on 168 patients (225 CTA timepoints) using standardized clinical data (OMOP CDM). XGBoost achieved the best performance ... read more 

Challenges in Using Clinical Data for AI-Enabled Diagnostic Support.

Studies in health technology and informatics May 21, 2026
Secondary use of clinical data for research and algorithm development can present challenges. Using a multi-hospital, retrospective dataset, we examined laboratory values and corresponding recorded diagnoses across common tests. Unanticipated finding... read more 

Integrating Nutritional Status in Machine Learning Predictive Models for Cardiovascular Risk: A Pilot Study.

Studies in health technology and informatics May 21, 2026
This study explored the use of machine learning (ML) models for cardiovascular risk stratification in an elderly Thai population. A cross-sectional analysis was performed in 210 hypertensive adults aged 60 years and older, using age, sex, systolic bl... read more 
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