BABY STEPS IN ARTIFICIAL INTELLIGENCE: DEVELOPMENT OF A JOS CARDIOVASCULAR DISEASE RISK APP TO IMPROVE SCREENING FOR CARDIOVASCULAR DISEASES.

Introduction/background: Assessing cardiovascular disease (CVD) risk is necessary in preventive cardiology. Studies have imputed CVD risk factors in algorithms to predict ASCVD. These various scores were derived from risk equations acquired from other populations.

BABY STEPS IN ARTIFICIAL INTELLIGENCE: DEVELOPMENT OF A JOS CARDIOVASCULAR DISEASE RISK APP TO IMPROVE SCREENING FOR CARDIOVASCULAR DISEASES.

Introduction/background: Assessing cardiovascular disease (CVD) risk is necessary in preventive cardiology. Studies have imputed CVD risk factors in algorithms to predict ASCVD. These various scores were derived from risk equations acquired from other populations.

Association of obesity anthropometric indices with hypertension, diabetes mellitus and hypertriglyceridemia in apparently healthy adult Nigerian population.

Background: Hypertension, hyperglycemia and hypertriglyceridemia are chronic conditions associated with cardiometabolic diseases. Certain anthropometric indices are known to predict them.

Aim: To investigate the association of anthropometric indices with these chronic diseases and which anthropometric index predicts them best.

Ultrasound assessed peri-renal fat: an index of sub-clinical atherosclerosis.

Objective: Overweight/obesity has predicted cardiovascular disease (CVD) risk for long with its standard measure of body mass index (BMI), which later was found to mis-classify risk oftentimes. This is because it does not differentiate between fat and whole body mass. The finding that fat especially visceral fat was more culpable shifted attention to ectopic fat as a more precise measure of CVD risk.