Available

Project reference

2026_P21_Zschaler_Arora

Start date

01/10/26

First Academic supervisor

Dr Steffen Zschaler

Second Academic supervisor

Dr Asit Arora

First Clinical supervisor

Mr Gareth Gwynn

4

Back to projects

Accessible and explainable AI pathway planning for cancer care

Successful cancer treatment requires early diagnosis and treatment. The NHS requires 75% of patients to receive a diagnosis within 28 days of initial referral and 85% to start treatment within 62 days of referral. While the 28-day target is often met, the 62-day target is only met for approx. 68% of patients, leading to adverse patient outcomes (with 56% GSTT is ranked 8th-lowest nationally (111/118 trusts)).
Achieving these targets requires careful management of complex cancer-care pathways, including different diagnostics, consultations, and treatments (surgery for ca. 50% of patients). Techniques for addressing such complex resource management and optimisation problems exist in the academic literature, but are underused in hospital practice.
This project will change this by co-creating, with clinical managers and surgeons, tools that are accessible, deliver explainable intervention proposals, and easily adapt to specific cancer types and pathways—for example through the application of AI approaches—delivering improved patient outcomes.