Five researchers using AI to transform health care

News & Announcements | 11 Feb 2025

[Clockwise from left] Drs. Amber Simpson, Farhana Zulkernine, Kerstin de Wit, Parvin Mousavi, Qingling Duan.

Highlighting faculty members in honour of International Day of Women and Girls in Science.

Each year on February 11, the United Nations celebrates the International Day of Women and Girls in Science. To mark the date, the Queen's Gazette shares the research work of five faculty members that are putting technology in the service of patients’ wellbeing and outcomes.

1. Machine learning for early cancer detection and metastasis forecasting – Amber Simpson

Cancer is a leading cause of death in Canada and worldwide. It is a complex disease that evolves differently in each patient, making clinical decision-making extra challenging. While physicians may not always detect key patterns in CT-scans, AI could help them gain insights that enhance diagnosis and treatment. Dr. Simpson (Biomedical and Molecular Science; School of Computing) is using state-of-the-art machine learning techniques to help forecast cancer spread. As the Canada Research Chair in Biomedical Computing and Informatics, her research will support clinical practice, improve patient outcomes, and unlock new possibilities in precision medicine.

2. Healthcare bots for patient triage and senior care – Farhana Zulkernine

Whether in hospitals or long-term care facilities, caring for patients requires assessing large amounts of information to make informed decisions. Dr. Zulkernine (School of Computing) is developing AI bots to streamline the decision-making process—for example, when triaging patients for emergency care. Building on existing triage systems, the bot collects patient symptoms and connects them with hospital data to better assess the urgency of their condition.

Dr. Zulkernine is also working on new voice assistant bots to best serve senior patients at home. The new technology can assist with medication reminders, offer guidance with challenging tasks, and provide a form of companionship, supporting healthy aging in a home environment.

3. Improving emergency care with faster pulmonary embolism detection – Kerstin de Wit

As an emergency medicine physician and Canada Research Chair in Emergency Venous Thromboembolism, Dr. de Wit (Emergency Medicine) understands the importance of agility and efficiency in care. She is exploring how AI can assist in diagnosing pulmonary embolism in the emergency department. She believes AI could help physicians detect the condition faster and is developing a model aiming to reduce misdiagnosis of this important condition.

4. Machine learning and genetics in disease risk and treatment outcomes – Qingling Duan

Our DNA influences more than the colour of our eyes or our hair—it also holds clues to why some people are more at risk for particular diseases and why some respond better to specific drug treatments than others. As the Queen's National Scholar in Bioinformatics, Dr. Duan (School of Computing; Biomedical and Molecular Science) uses machine learning and bioinformatics to investigate how genetics play a role in drug response and in diseases like asthma—which affects millions of Canadians, especially children. Her work on respiratory diseases led Dr. Duan to engage in other studies into early childhood health, including groundbreaking research on how genes influence the composition of health-boosting ingredients in human breast milk.

5. AI solutions for computer-assisted surgery and medical interventions – Parvin Mousavi

Big data and machine learning are key components in the work of Dr. Mousavi (School of Computing; Pathology and Molecular Medicine; Medicine; and Biomedical and Molecular Science). Focusing on precision medicine, she is looking for better solutions in patient-specific diagnostics, treatments, and clinical interventions. As the Canada Research Chair in Medical Informatics, Dr. Mousavi’s interdisciplinary research program integrates medical imaging, computer-assisted interventions, computational biology, and bioinformatics, applying actionable machine learning methods to derive healthcare innovation and transform clinical decision making. To translate research results into clinical practice, Dr. Mousavi also leads a national training program in medical informatics.

The original version of this announcement appeared on The Gazette.