F1 score

Biomarker1 paper1 finding

In silico1

Interventions

1

Prompt engineering

upin silico1Very low certainty

1 study

Prompt engineering improves F1 score in silico.
In silicon = 117,698
Atherosclerosis prediction with large language models via prompt engineering · Journal of human hypertension · 7 Sep 2026

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Latest

74

Journal of Imaging Informatics in MedicineIn silicoYesterday

An Automated Machine Learning Based Framework for Scan Level Coronary Artery Calcium Risk Stratification

Coronary artery disease

European Spine JournalHumans5 Oct

Machine learning-assisted osteoporosis detection using radiographic canal bone ratio (CBR-7) and demographic features

Frontiers in MedicineHumans2 Oct

Development and validation of a LASSO-selected machine learning prediction pipeline for predicting coronary artery calcification in a health check-up population

Frontiers in Public HealthHumans2 Oct

Predicted 10-year cardiometabolic risk among hospital staff: a cross-sectional study

SensorsIn silico1 Oct

Development of a Wearable Sensor Platform for Fall Risk Assessment and Fall Detection

Frontiers in PhysiologyHumans1 Oct

Spatially resolved longitudinal changes in tibial subchondral trabecular bone texture for exploratory prediction of incident knee osteoarthritis

Oral Health & Preventive DentistryHumans30 Sep

Analysis of Dietary Patterns Containing Curcumin and Oral Cancer

Research SquareIn silicoPreprint26 Sep

Explainable Machine Learning Framework to Prioritize Predictors of Type 2 Diabetes Risk Among Adult Males Using Lifestyle and Clinical Indicators

Type 2 diabetes

DiagnosticsHumans26 Sep

Screening Signals of Reference-Defined Metabolic Syndrome Using HbA1c and LDL Cholesterol: An Explainable Machine Learning Study

HDL cholesterol

BioengineeringIn silico26 Sep

DiAbot: A Conversational AI System Coupling Large Language Models with an Interpretable Decision Tree for CDR-Style Dementia Screening