My AI-Guided Ultrasound System for Real-Time Scanning Optimization and Skill Transfer helps non-expert operators optimize scans and learn probe positioning. The project received First Place in the Graduation Project and Second Place in the Research to Impact Competition.
At the Biomedical Informatics Research Unit, Nile University, I investigated machine learning approaches to predict ovarian cancer subtypes from gene-expression datasets. I applied resampling and feature-selection techniques to address class imbalance.
I also trained and evaluated deep learning models for ovarian tumor classification using ultrasound datasets. In a separate genomic sequencing project, I analyzed data in R and developed a software benchmark selected among the Top 10 posters.
