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A single-cell transcriptomic analysis of endometriosis, endometriomas, eutopic endometrial samples and uninvolved ovary tissues highlights cell populations characteristic of these tissue types. Transcriptional and cellular heterogeneity across tissues suggests novel therapeutic targets and biomarkers for this disease.
An AI-based decision support system for ovarian cancer diagnosis, based on our research leveraging ML and Explainable AI. The system predicts cancer risk and explains decisions to aid healthcare professionals.
A full-stack ML-powered web application for early risk prediction of Ovarian Cancer, PCOS, and Hepatitis B, enabling data-driven clinical decision support.
This R code analyses the influence of 2x PARP inhibitors on the presence of 4x immune checkpoint proteins (PD-1, PD-L1, CTLA-4 & SIRP) in a group of Ovarian Cancer patients pre, during and post treatment.