Innovative label-free lymphoma diagnosis using infrared spectroscopy and machine learning on tissue sections.

ABSTRACT: The diagnosis of lymphomas is challenging due to their diverse histological presentations and clinical manifestations. There is a need for inexpensive tools that require minimal expertise and are accessible for routine laboratories. Contrastingly, current conventional diagnostic methods are often found only in specialized environments. Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy offers a nondestructive and user-friendly approach in the analysis of a wide range of samples. In this paper, we determined whether the technique coupled with machine learning can detect and differentiate lymphoma within lymphoid tissue samples. Tissue sections from 295 individuals diagnosed with lymphoma and 389 individuals without the disease were analyzed using ATR-FTIR spectro

SUBMITTER: Delrue C 

PROVIDER: S-EPMC11528060 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature