Near-Infrared Spectroscopy with Supervised Machine Learning as a Screening Tool for Neutropenia.

ABSTRACT: The use of non-invasive tools in conjunction with artificial intelligence (AI) to detect diseases has the potential to revolutionize healthcare. Near-infrared spectroscopy (NIR) is a technology that can be used to analyze biological samples in a non-invasive manner. This study evaluated the use of NIR spectroscopy in the fingertip to detect neutropenia in solid-tumor oncologic patients. A total of 75 patients were enrolled in the study. Fingertip NIR spectra and complete blood counts were collected from each patient. The NIR spectra were pre-processed using Savitzky-Golay smoothing and outlier detection. The pre-processed data were split into training/validation and test sets using the Kennard-Stone method. A toolbox of supervised machine learning classification algorithms was applied to t

SUBMITTER: Raposo-Neto JJ 

PROVIDER: S-EPMC10817549 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature