Quantum Machine learning for medical imaging – radiology, ophthalmology and diabetes prediction

This project explores how quantum computing and artificial intelligence (AI) can work together to improve how we detect diseases using medical images. Medical imaging, like X-rays, clinical photos, and eye scans, are essential for diagnosing many health conditions. However, analyzing these images quickly and accurately remains a challenge, especially as the amount of data continues to grow.

By combining the power of AI with the emerging capabilities of quantum computing, this research aims to develop Quantum Machine Learning algorithms in order to create smarter, faster, and more reliable tools for identifying diseases. The project focuses on three key areas: detecting lung conditions from chest X-rays, identifying diabetic foot ulcers from clinical images, and spotting retinal diseases from eye scans.

Ultimately, this project supports the development of next-generation healthcare tools that could lead to earlier diagnoses, better treatment decisions, and improved patient outcomes. It also helps build Canada’s leadership in digital health and quantum innovation by training future experts in these fast-growing fields.

Faculty Supervisor:

Moulay Akhloufi

Student:

Partner:

Université Ibn Tofaïl

Discipline:

Computer science

Sector:

Quantum Science; Artificial Intelligence; Health and Related Sciences and Technology

University:

Université de Moncton

Program: