Predicting dyslipidemia incidence: unleashing machine learning algorithms on Lifestyle Promotion Project data

• Egile Nagusiak: Senobar Naderian (Egilea), Zeinab Nikniaz (Egilea), Mahdieh Abbasalizad Farhangi (Egilea), Leila Nikniaz (Egilea), Taha Sama-Soltani (Egilea), Parisa Rostami (Egilea)
• Formatua: Liburua
• Argitaratua: BMC, 2024-07-01T00:00:00Z.
• Gaiak: article
• Sarrera elektronikoa: Connect to this object online.

Abstract Background Dyslipidemia, characterized by variations in plasma lipid profiles, poses a global health threat linked to millions of deaths annually. Objectives This study focuses on predicting dyslipidemia incidence using machine learning methods, addressing the crucial need for early identif...