Research implementation on supporting medical diagnosis under incomplete data.

Two or three subtypes of high grade serous ovarian cancer subtypes fit data from different populations better than four

Analysis of treatment naive and neo-adjuvant chemotherapy treated high-grade serous ovarian cancer samples

🧠Deep Learning-based✔️ Ovarian Cancer🙅🏻‍♀️ Subtypes Identification using Multi-Omics Data✅

MSDS Thesis - Pan-Collagen Survival Analysis of CNV in Ovarian Cancer

[EMBC 2022] Multi-agent Feature Selection for Integrative Multi-omics Analysis

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.

Implements four major subtype classifiers for high-grade serous (HGS) ovarian cancer.

Proteomics and IHC data analysis for LGSC and SBT tumour microenvironment study.

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.

Quantitatively evaluate tumor stroma reaction within ovarian cancers, and establish assocaitaions to prognosis, molecular signatures.

Clinical oncology tumor board decision support system made by the Decider project.