aceInfrared spectroscopy with statistical analysis and machine learning for cancer risk assessment in inflammatory bowel disease patients
Patients with inflammatory bowel disease (IBD) undergo regular colonoscopic surveillance due to their elevated risk of developing colorectal cancer (CRC). However, current clinical, endoscopic and histopathological risk stratification methods can be limited in sensitivity and objectivity, highlighting the need for complementary molecular approaches. In this study, Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) was used to acquire mid-infrared (MIR) spectra from IBD-associated end…
Infrared spectral fingerprints of IBD biopsies, especially in a lipid-associated region, carried information linked to long-term colorectal cancer risk, suggesting a possible complement to surveillance.
Machine learning classifiers trained on 30 patients' biopsy spectra did not perform better than chance, so no definitive risk classifier could be established.
The cohort of 30 patients is too small to establish a definitive classifier, and classifier performance was not significantly above chance.
Evidence
- Peer-reviewedThe Analyst2026-10-13
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Truvace Impact Record TRV-2026-2047, v1: “Infrared spectroscopy with statistical analysis and machine learning for cancer risk assessment in inflammatory bowel disease patients.” Truvace, 2026-10-20. /record/TRV-2026-2047 (accessed at citation time). sha256 33f159b325258f57…
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