Using AI to predict how cancers respond to drugs, accepted at an IEEE conference
Two patients with the same cancer can respond completely differently to the same drug, and much of that difference is written in their biology. Arfa built machine learning models that combine multiple layers of biological data, known as multi-omics, to predict how cancers will respond to specific drugs. The goal is to help match patients to the treatments most likely to work for them. Her paper was accepted at an IEEE conference.
Medical AI & Oncology
First-author paper accepted at an IEEE conference
IEEE, 2026
An 11th grader at St. Mary Academy Bay View with an interest in AI and biology and no research experience.
First author of an AI study on predicting cancer drug response from multi-omics data, accepted at an IEEE conference.
First-author paper accepted at an IEEE conference
Combined multiple layers of biological data to predict drug response
Research aimed at matching cancer patients to effective treatments
Started from zero research experience in 11th grade
Mohammed Alnuwaiser, First-author paper accepted at an IEEE conference