Artificial Intelligence Medical Compendium

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

Showing 12,711 to 12,720 of 210,436 articles

Prediction of Early Functional Outcome After Acute Ischemic Stroke Using Real-World Clinical Data in Vietnam and Indonesia: Retrospective Cohort Study.

Studies in health technology and informatics May 21, 2026
Accurate prediction of early functional outcome after acute ischemic stroke is critical for clinical decision-making. This retrospective cohort study developed and externally validated a machine learning model using routine clinical data from two set... read more 

Feasibility of Causality-Aware Machine Learning for Drug Safety on OMOP-CDM.

Studies in health technology and informatics May 21, 2026
Regulators increasingly view real-world healthcare data and potential use of Artificial Intelligence (AI) approaches as vital for pharmacovigilance (PV). Large European and global initiatives have invested in the development of scalable pharmacovigil... read more 

Explainable ML for Predicting Vision Loss in Pediatric NF-1 Patients Using OCT Data.

Studies in health technology and informatics May 21, 2026
We applied explainable machine learning to optical coherence tomography (OCT) data from 168 pediatric NF-1 patients to predict vision abnormalities. The Balanced Random Forest model achieved an AUC-ROC of 0.82. SHapley Additive exPlanations (SHAP) an... read more 

Supervised Learning Provides Small but Consistent Improvements to Clustering when Predicting Chronic Pain Outcomes Following Treatment.

Studies in health technology and informatics May 21, 2026
Using registry and questionnaire data from 47,235 chronic pain patients, we evaluated whether supervised learning outperforms clustering in predicting nine one-year outcomes. Supervised models showed small but consistent improvements (best RMSE 5.49 ... read more 

Robustness of Healthcare ML Under Data Quality Degradation: A Dimension-Wise Analysis on MIMIC-IV.

Studies in health technology and informatics May 21, 2026
Using the MIMIC-IV database (1,500-7,000 patients), we assess the robustness of healthcare machine learning models under controlled data quality (DQ) degradations applied to training or test data across five dimensions. Model performance declined wit... read more 

Extending Grad-CAM to DualNet.

Studies in health technology and informatics May 21, 2026
The machine learning architecture DualNet was introduced for analysing both frontal and lateral X-rays of a patient for disease classification. Since the model lacks explainability methods, we extended the pytorch-grad-cam package for the application... read more 

Automated Segmentation of Tissue Zones in Distraction Osteogenesis.

Studies in health technology and informatics May 21, 2026
Automated analysis of histological sections in distraction osteogenesis can reduce manual effort and subjectivity in histological assessment. A 2D nnU-Net was trained to segment three characteristic tissue zones in sections of rat tibial distraction ... read more 

Norovirus in the UK Biobank: Silver-Standard Labels, Semi-Supervised Models.

Studies in health technology and informatics May 21, 2026
Researching norovirus gastroenteritis retrospectively is challenging, since the absence of a disease record does not imply the absence of that disease. We compared three classification approaches in the UK Biobank: silver-standard labeled controls on... read more 

Temporal Query Answering for the Scheduling of Multiple Clinical Guidelines.

Studies in health technology and informatics May 21, 2026
Clinical guidelines are widely used in the medical practice. Temporal constraints-such as durations, intervals, and delays-are an intrinsic component of most guidelines. Existing approaches to computerized clinical guidelines (CIGs) typically include... read more 

A Comparison of Different Models to Recommend Variables for Research Data Requests to German Cancer Registries.

Studies in health technology and informatics May 21, 2026
Cancer registry data is an important resource in cancer research, e.g. to formulate hypotheses for new interventions, to identify recruitment potentials for clinical trials or to evaluate side effects of new interventions on a large population, but r... read more 
Popular Topics
Recent Journals