Mathematical Modeling of Nir Spectroscopy Data and Development of a Diagnostic Model Based on Artificial Intelligence
Year: 2026
Type: conference-paper
Abstract: The paper presents the development of a diagnostic model based on near- infrared(NIR) spectroscopy data using artificial intelligence methods. Spectral signals are preprocessed andmathematically modeled. The modeling is based on the Beer–Lambert law, and the J criterion is usedto evaluate signal quality. The obtained results demonstrate the effectiveness of the proposed model.The maximum J value reached 6.57, while for the simple method it was4.75. The overall accuracy of the model ranged from 85% to 92%. In some cases, a decrease inaccuracy was observed due to noise and external factors. The proposed approach is effective fordetecting optical changes in biological tissues and for early disease diagnosis.
DOI: 10.65164/b3182r59
Institution: Osh Technological University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W7166320844