Artificial Intelligence for Kidney Stone Spectra Analysis: Using Artificial Intelligence Algorithms for Quality Assurance in the Clinical Laboratory.

ABSTRACT:

Objective

To determine if a set of artificial intelligence (AI) algorithms could be leveraged to interpret Fourier transform infrared spectroscopy (FTIR) spectra and detect potentially erroneous stone composition results reported in the laboratory information system by the clinical laboratory.

Background

Nephrolithiasis (kidney stones) is highly prevalent, causes significant pain, and costs billions of dollars annually to treat and prevent. Currently, FTIR is considered the reference method for clinical kidney stone constituent analysis. This process, however, involves human interpretation of spectra by a qualified technologist and is susceptible to human error.

Methods

This prospective validation study was conducted from October 29, 2020, to October 28, 2021, to test

SUBMITTER: Day PL 

PROVIDER: S-EPMC11975758 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature