Lipid monitoring using non-invasive measurement technologies and machine learning: a systematic review.

ABSTRACT:

Background

Cardiovascular diseases (CVD) are the leading cause of death among women, with risk increasing after menopause. Lipid levels are key biomarkers, yet conventional blood tests remain invasive and underutilized. Non-invasive technologies and machine learning (ML) may offer new approaches to lipid monitoring and risk assessment using wearable devices and biosensors.

Objective

This systematic review investigates the availability, accuracy, and clinical applicability of minimally and non-invasive lipid monitoring methods and ML-based cardiovascular risk estimation in adults.

Methods

A systematic search was conducted in MEDLINE, Embase, Cochrane Library, Web of Science, Scopus, and ClinicalTrials.gov (2010-2024). Studies in English were included; case reports and

SUBMITTER: Endrass J 

PROVIDER: S-EPMC12858588 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature