Prediabetes risk classification algorithm <i>via</i> carotid bodies and K-means clustering technique.

ABSTRACT: Diabetes is a disease that affects millions of people in the world and its early screening prevents serious health problems, also providing relief in the demand for healthcare services. In the search for methods to support early diagnosis, this article introduces a novel prediabetes risk classification algorithm (PRCA) for type-2 diabetes mellitus (T2DM), utilizing the chemosensitivity of carotid bodies (CB) and K-means clustering technique from the field of machine learning. Heart rate (HR) and respiratory rate (RR) data from eight volunteers with prediabetes and 25 without prediabetes were analyzed. Data were collected in basal conditions and after stimulation of the CBs by inhalation of 100% of oxygen and after ingestion of a standardized meal. During the analysis, a greater variability

SUBMITTER: Pinheiro RF 

PROVIDER: S-EPMC11784710 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature