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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
Vascular graph network for ovarian lesion classification using optical-resolution photoacoustic microscopy.

Diagnosing ovarian lesions is challenging because of their heterogeneous clinical presentations. Some benign ovarian conditions, such as endometriosis, can have features that mimic cancer. We use optical-resolution photoacoustic microscopy (OR-PAM) …

Published: Dec. 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
Artificial intelligence applications in endometriosis imaging.

Artificial intelligence (AI) may have the potential to improve existing diagnostic challenges in endometriosis imaging. To better direct future research, this descriptive review summarizes the general landscape of AI applications …

Published: April 1, 2025, midnight
BCL6 (B-cell lymphoma 6) expression in adenomyosis, leiomyomas and normal myometrium.

Adenomyosis and leiomyomas are common benign uterine disorders characterized by abnormal cellular proliferation. The BCL6 protein, a transcriptional repressor implicated in cell proliferation and oncogenesis, has been linked to the …

Published: Feb. 4, 2025, midnight
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