A machine learning approach to predict pancreatic islet grafts rejection versus tolerance.

ABSTRACT: The application of artificial intelligence (AI) and machine learning (ML) in biomedical research promises to unlock new information from the vast amounts of data being generated through the delivery of healthcare and the expanding high-throughput research applications. Such information can aid medical diagnoses and reveal various unique patterns of biochemical and immune features that can serve as early disease biomarkers. In this report, we demonstrate the feasibility of using an AI/ML approach in a relatively small dataset to discriminate among three categories of samples obtained from mice that either rejected or tolerated their pancreatic islet allografts following transplant in the anterior chamber of the eye, and from naïve controls. We created a locked software based on a support ve

SUBMITTER: Ceballos GA 

PROVIDER: S-EPMC7644021 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature