A student-led initiative harnessing AI to revolutionise medical imaging — building solutions for disease classification and detection.
Monash AIM is a student-led initiative harnessing the power of AI to revolutionise medical imaging. We're developing innovative solutions for disease classification and detection, using a diverse skillset that includes Python, machine learning, and image processing.
We AIM to be at the forefront of AI-driven medical imaging solutions, enabling the advancement of clinical practice by bringing passionate students from various disciplines together to collaborate and create innovative solutions.
CNNs, transfer learning, and explainable AI — built in Python with TensorFlow and PyTorch.
Models shaped by medical students and clinicians who know what accuracy means in practice.
IT and medical faculties side by side — diverse thought turns research into real impact.
Explore AIM's innovative projects and witness how we're transforming healthcare through AI. Our work showcases our team's dedication, skills, and passion.
Generalised Analysis of Vessels in Eye.
Accurate vessel measurements — widths, arteriovenous ratio, vessel density, and branching complexity — give doctors clinically meaningful biomarkers for diagnosing both eye and whole-body conditions.
View project →Combining histology, medical imaging and molecular data for prognosis and diagnosis.
Prostate cancer is the 4th most common cancer worldwide, yet current pathways drive overdiagnosis and invasive biopsies. Transparent AI decision support could reduce unnecessary, risky procedures.
View project →Efficient AI technologies for multimodal management of tuberculosis.
A shortage of trained radiologists makes TB screening slow and subjective. In the regions where TB claims the most lives, AI can widen access to fast, consistent diagnosis and treatment.
View project →Extracting executable cohort definitions for medical imaging research.
There is no benchmark structure for cohort selection criteria, making imaging studies hard to reproduce. Standardised, computable criteria improve reproducibility and fairness in future research.
View project →Detecting stroke in brain scans with machine learning.
An ischemic stroke occurs when a vessel supplying blood to the brain is blocked. Fast, automated detection supports earlier intervention when every minute counts.
View project →As AIM, we are driven by the potential of AI and medicine converging to revolutionise healthcare, striving to transform lives and create a healthier future for all.
As a student-led team, we believe in the power of collaboration and diversity of thought. We can't wait to show you what we've been working on!
Meet the dedicated students behind AIM, driven by the convergence of AI and medicine to shape the future of healthcare.
Recruitment is currently closed for Semester 1 2026 — positions open in Semester 2!