SMU researcher using machine learning to improve lung cancer treatment
From the Springboard Content Lab
A researcher from Springboard member Saint Mary’s University is using machine learning to improve treatment for lung cancer which remains one of the most complex diagnoses in modern medicine.
Dr Somayeh Kafaie is working with Nova Scotia Health and Springboard member Cape Breton University to explore data-driven models to design personalized and precise care plans for the disease. The goal of the research is to reduce delays in treatment and minimize risk to surrounding organs.
“For me, my research is about hope and progress. It’s about making sure every patient receives the right treatment at the right time.”
Dr Somayeh Kafaie, assistant professor of mathematics and computing science, SMU
Data science meets patient need
Dr. Kafaie leads the GraphML Lab, which combines data science with human needs. Supported by a Legacy Research Grant from the Lung Association of Nova Scotia & Prince Edward Island, her project applies machine learning to make lung cancer radiation treatment faster, safer and more personalized.
The work explores whether artificial intelligence can help doctors predict the best radiation treatment plan for each patient based on their anatomy, medical history and the unique position of their tumour.
Dr. Kafaie and her team are using data-driven models to help physicians design more precise, individualized care plans, reducing delays and minimizing risk to surrounding organs.
“Right now, creating a radiation treatment plan can take several days. It requires multiple rounds of adjustment by medical teams before it’s finalized. We’re exploring how machine learning can act as an intelligent assistant; not replacing doctors but helping them predict the right settings more efficiently and with greater confidence.”
Dr Kafaie
Research aims to reduce wait times, personalize treatment plans
Lung cancer remains one of the most aggressive and least forgiving cancers, touching almost every family in some way. For patients and their loved ones, waiting for treatment can be excruciating. A technology that shortens the wait time while improving accuracy could change outcomes and lives.
Dr. Kafaie’s collaboration with Dr. Mike Sattarivand at Nova Scotia Health began with a simple question: Can we make lung cancer treatment planning faster and more precise? That question has since evolved into a cross-disciplinary partnership combining medical expertise with advanced analytics.
Students in Dr. Kafaie’s lab gain hands-on experience using data science to solve real-world problems. The collaboration with Nova Scotia Health strengthens the connection between academic research and patient-centred innovation.
“SMU provides the academic foundation in data science and machine learning that makes this research possible. Our students work closely with clinical experts, attending our lab meetings and contributing to the computational models. It’s truly a bridge between the university and the health-care system.”
Dr. Kafaie
Data-driven solutions can be applied to other diseases
The project focuses on lung cancer, but the same algorithms could be used to inform treatment of other cancers and diseases where personalized care is critical.
“This is just the beginning,” Dr. Kafaie says. “AI can be a support system for doctors across many areas of medicine.”
Saint Mary’s University is a member of the Springboard Network of 10 post-secondary institutions in Atlantic Canada. Our mission is to grow the economy through industry and community collaborations and research commercialization.