This research applies machine learning to genetic data to distinguish harmless DNA variations from cancer-causing mutations. By treating DNA like a crime scene, the model learns to identify which genetic changes truly drive breast cancer risk, supporting more accurate diagnosis and informed clinical decision-making.

Hip dysplasia is often diagnosed too late or too inconsistently, leading to lifelong pain. The speaker’s research builds the first open-access AI tool for detecting and studying the condition, enabling portable automated diagnosis and global collaboration. By sharing tools instead of guessing, researchers can reduce unnecessary surgeries and improve outcomes worldwide.