Artificial Neural Processing-Driven Bioelectronic Nose for the Diagnosis of Diabetes and Its Complications.

ABSTRACT: Diabetes and its complications affect the younger population and are associated with a high mortality rate; however, early diagnosis can contribute to the selection of appropriate treatment regimens that can reduce mortality. Although diabetes diagnosis via exhaled breath has great potential for early diagnosis, research on such diagnosis is restricted to disease detection, requiring in-depth examination to diagnose and classify diseases and their complications. This study demonstrates the use of an artificial neural processing-based bioelectronic nose to accurately diagnose diabetes and classify diabetic types (type I and II) and their complications, such as heart disease. Specifically, an M13 phage-based electronic nose (e-nose) is used to explore the features of subjects with diabetes a

SUBMITTER: Jang WB 

PROVIDER: S-EPMC11469111 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature