Biomarker identification and point-of-care assessment in urosepsis supported by machine learning

Pawel Wityk; Kacper Cierpiak; Joanna Raczak-Gutknecht; Mariusz Siemiński; Jacek Szypenbejl; Beata Krawczyk; Michal Markuszewski; Malgorzata Szczerska

doi:10.1117/12.3017006

20 June 2024 Biomarker identification and point-of-care assessment in urosepsis supported by machine learning

Pawel Wityk, Kacper Cierpiak, Joanna Raczak-Gutknecht, Mariusz Siemiński, Jacek Szypenbejl, Beata Krawczyk, Michal Markuszewski, Malgorzata Szczerska

Author Affiliations +

Proceedings Volume 13008, Biophotonics in Point-of-Care III; 130080L (2024) https://doi.org/10.1117/12.3017006
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Conference Poster

Abstract

Urinary tract infections (UTIs) are prevalent clinical conditions that, if untreated, can progress to urosepsis, a potentially fatal systemic infection. Timely detection and accurate assessment are critical for effective intervention. This presentation will show the integration of Liquid Chromatography-Mass Spectrometry (LC-MS)-based metabolomics and proteomics to advance our comprehension of UTI and urosepsis. Emphasis is placed on biomarker discovery and the development of a Point-of-Care (PoC) device for urosepsis assessment using urine samples.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Pawel Wityk, Kacper Cierpiak, Joanna Raczak-Gutknecht, Mariusz Siemiński, Jacek Szypenbejl, Beata Krawczyk, Michal Markuszewski, and Malgorzata Szczerska "Biomarker identification and point-of-care assessment in urosepsis supported by machine learning", Proc. SPIE 13008, Biophotonics in Point-of-Care III, 130080L (20 June 2024); https://doi.org/10.1117/12.3017006

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