AI Tool Predicts Organ Dysfunction During Chemotherapy Treatment
Scientists create AI-driven system for tailoring chemotherapy treatments
An innovative AI tool, developed in collaboration with researchers from Durham University's top-ranked Computer Science department, Evergreen Life, UCL, UCLPartners, clinicians from UCL Hospitals, and other NHS trusts, is set to revolutionise the management of chemotherapy treatment for cancer patients.
The AI model, which has demonstrated high accuracy in early findings, aims to reduce the number of blood tests needed for low-risk patients by predicting the risk of kidney and liver dysfunction during treatment. This could potentially reduce hospital visits for many patients.
The model incorporates routinely collected electronic health records and results from blood tests taken during the previous two cycles of chemotherapy treatment. It predicts the likelihood of organ dysfunction at later cycles, allowing doctors to tailor the frequency of future blood tests based on an individual patient's risk profile.
The project aligns with the ethos of enhancing wellbeing through research, and the AI tool was optimised to perform well even when applied to new hospitals where patient data may be recorded differently. The initial focus of the AI tool is on breast, colorectal, and Diffuse Large B-Cell Lymphoma cancers.
The work of Dr Noura Al Moubayed and Dr Matthew Watson, along with their teams, has been instrumental in the development of this AI tool. The project was funded by an Innovate UK Biomedical Catalyst Grant, and the next steps include deploying the AI tool in additional UK clinics and collecting further data to expand its utility across cancer types.
AI tools in healthcare are increasingly used to predict organ dysfunction by analysing patient data, medical histories, and treatment outcomes. These tools often employ machine learning algorithms to identify patterns that may indicate early signs of kidney or liver dysfunction. By identifying high-risk patients early, healthcare providers can tailor treatment plans to reduce the risk of organ damage, potentially reducing the need for hospital visits.
Visit the websites of Evergreen Life and UCL Partners to learn more about the work of Dr Noura Al Moubayed and Dr Matthew Watson, and explore undergraduate and postgraduate courses offered by the Department of Computer Science at Durham University, which is growing with ambitious plans for the future and an inclusive, vibrant, and international community.
- This AI tool, developed for chemotherapy treatment management, focuses on predicting chronic kidney disease and liver dysfunction in cancer patients, potentially reducing hospital visits for low-risk patients.
- The project's innovative AI model is designed to incorporate routine health records and previous chemotherapy treatment results to identify the risk of organ dysfunction, allowing doctors to adjust test frequencies according to individual risk profiles.
- The AI tool's initial focus is on breast, colorectal, and Diffuse Large B-Cell Lymphoma cancers, but plans include deploying it in additional UK clinics and expanding its utility across various cancer types.
- The collaboration between researchers, clinicians, and NHS trusts leverages technology, artificial intelligence, and--specifically--machine learning algorithms to analyze patient data, medical histories, and treatment outcomes to predict early signs of organ dysfunction, improving health and wellness for cancer patients.
