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Artificial intelligence (AI) is rapidly transforming healthcare, offering unprecedented opportunities to improve patient outcomes, reduce costs, and accelerate medical discoveries. As someone working at the intersection of mathematics and medicine, I've witnessed firsthand how computational approaches are reshaping our understanding of disease and treatment. Current Applications AI's impact in healthcare spans multiple domains. In medical imaging, deep learning algorithms now match or exceed human radiologists in detecting certain cancers, identifying diabetic retinopathy, and spotting early signs of Alzheimer's disease. These systems analyze thousands of images in seconds, flagging potential issues for human review and enabling earlier interventions. ...

Imagine visiting your doctor and receiving a treatment plan designed specifically for you—not just based on your symptoms, but on complex mathematical calculations that predict how your unique biology will respond to different therapies. This is the promise of personalised medicine, and mathematical models are making it a reality. What Is Personalised Medicine? Personalised medicine moves away from the traditional "one-size-fits-all" approach to healthcare. Instead of prescribing the same treatment to every patient with a particular condition, doctors can now consider individual differences in genetics, lifestyle, and disease characteristics to select the most effective therapy with the fewest side effects. ...

Cancer is not just a biological problem. It is also a mathematical one. Tumours grow, compete for oxygen, respond to drugs, and adapt to stress — all in ways that can be described, modelled, and predicted using mathematics. Mathematical oncology is the field that does exactly this. What does a mathematical oncologist actually do? At its core, mathematical oncology uses equations to describe how cancer behaves. Just as engineers use mathematics to predict how a bridge will hold weight, or meteorologists use it to forecast weather, mathematical oncologists use it to predict how a tumour will grow, shrink, or resist treatment. ...