Area of research
Cancer Research · Artificial Intelligence
Research interest
Research interests include Breast Cancer Treatment Studies, AI in cancer detection, Cervical Cancer and HPV Research, and Endometrial and Cervical Cancer Treatments.
Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer
Image‐based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno‐oncology Biomarker Working Group on Breast Cancer
Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer
Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer
Predicting Neoadjuvant Treatment Response in Triple-Negative Breast Cancer Using Machine Learning
Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
A spatial attention guided deep learning system for prediction of pathological complete response using breast cancer histopathology images
A Case Series Exploration of Multi-Regional Expression Heterogeneity in Triple-Negative Breast Cancer Patients
Crown-Like Structures in Breast Adipose Tissue: Early Evidence and Current Issues in Breast Cancer
Protein Conformational Changes in Breast Cancer Sera Using Infrared Spectroscopic Analysis
Combined HER3-EGFR score in triple-negative breast cancer provides prognostic and predictive significance superior to individual biomarkers
Prognostic Role of Androgen Receptor in Triple Negative Breast Cancer: A Multi-Institutional Study
Serum concentrations of active tamoxifen metabolites predict long-term survival in adjuvantly treated breast cancer patients
Amplified centrosomes and mitotic index display poor concordance between patient tumors and cultured cancer cells