Journal of the Egyptian National Cancer Institute
Jan 5, 2026
BACKGROUND: Ovarian cancer remains the most lethal gynecological malignancy, necessitating precise diagnostic strategies to improve patient outcomes. This study aims to develop and evaluate machine learning models that utilize patient history, imagin...
We report a proof-of-concept diagnostic strategy that integrates multiplexed Raman-tagged antibody labeling with label-free surface-enhanced Raman spectroscopy (SERS) and machine learning (ML) to improve the detection of ovarian cancer via extracellu...
Comprehensive biomedical proteomic datasets are accumulating exponentially, warranting robust analytics to deconvolute them for identifying novel biological insights. Here, we report a strategic machine learning (ML)-based feature extraction workflow...
Cancer control : journal of the Moffitt Cancer Center
Jan 1, 2021
BACKGROUND: The differential diagnosis of ovarian cancer is important, and there has been ongoing research to identify biomarkers with higher performance. This study aimed to evaluate the diagnostic utility of combinations of cancer markers classifie...
OBJECTIVES: The aim of the study was to assess the role of HE4 and CA125 in differentiation between malignant and non-malignant endometrial pathologies.
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