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FTIR Spectroscopy Combined with Machine Learning Reveals Molecular Signatures Distinguishing three Phenotypes of Endometriosis.

Endometriosis is a chronic inflammatory disorder in which endometrial tissue grows outside the uterus, leading to pelvic pain and infertility. It remains a major challenge in women's health due to …

Published: Jan. 5, 2026, midnight
Biochemical Heterogeneity of Endometriosis Phenotypes Revealed by FTIR Analysis.

Fourier-transform infrared (FTIR) spectroscopy was used to investigate molecular differences among peritoneal, ovarian, bowel endometriosis phenotypes and control tissues. Peritoneal lesions showed the most pronounced spectral changes in CH-stretching (2800-3000 …

Published: Nov. 30, 2025, midnight
Detection of peritoneal, ovarian, and bowel endometriosis using FTIR spectroscopy and machine learning.

This study evaluated the diagnostic potential of Fourier-transform infrared (FTIR) spectroscopy combined with machine learning for the detection of ovarian, bowel, and peritoneal endometriosis. The Boruta algorithm was applied to …

Published: Nov. 23, 2025, midnight
A machine learning approach towards endometriosis screening using infrared spectra of urine.

Endometriosis diagnosis is challenging due to non-specific symptoms that overlap with other gynaecological conditions. This study proposes a non-invasive Machine Learning (ML) ‒ based urine test using Attenuated Total Reflection …

Published: Sept. 6, 2025, midnight
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