IEEE

Classification of Diabetic Patients Using a Network Representation of Their Metabolism

Abstract: Studies on Type 2 Diabetes Mellitus (T2DM) rely on specific metabolic networks to represent the intricate relationships between metabolites. Accurate classification requires analyzing ...
Frontiers

Explainable machine learning for stroke risk prediction: a comparative study with SHAP-based interpretation

Background: Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear ...
IEEE

EffNet-SVM: A Hybrid Model for Diabetic Retinopathy Classification Using Retinal Fundus Images

Abstract: The manual diagnosis of diabetic retinopathy (DR) is often invasive, time-consuming, expensive, and prone to human error. Additionally, it can be subjective ...
Frontiers

Bridging traditional and conventional knowledge for soil classification in landslide-prone areas using exploratory factor analysis

1 ACS Lab, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India 2 Geohazard Studies Laboratory, Indian Institute of Technology Kamand, Mandi, Himachal Pradesh, India Introduction: ...