Researchers have created new artificial intelligence (AI) machine learning software that can forecast the survival rates and response to treatments of patients with ovarian cancer.
The software, created by researchers at Imperial College London and the University of Melbourne, has been able to predict the prognosis of patients with ovarian cancer more accurately than current methods, and can also predict what treatment would be most effective for patients following diagnosis.
Researchers say that this new technology could help clinicians administer the best treatments to patients more quickly, and also paves the way for more personalised medicine.
They hope that the technology can be used to stratify ovarian cancer patients into groups based on the subtle differences in the texture of their cancer on computerised tomography (CT) scans rather than classification based on what type of cancer they have, or how advanced it is.
Health minister, Nicola Blackwood said of the technology: “Artificial intelligence has huge potential to revolutionise healthcare by offering more accurate and earlier diagnoses – it could transform the lives of cancer patients in the future. We must embrace this type of technology to enable clinicians to provide the best possible care on the NHS which is personalised to individuals.”
Ovarian cancer is the sixth most common cancer in women and usually affects women after the menopause or those with a family history of the disease, with 6,000 new cases of ovarian cancer a year in the UK.
Doctors currently diagnose ovarian cancer in a number of ways including a blood test to look for a substance called CA125 – an indication of cancer – followed by a CT scan that uses x-rays and a computer to create detailed pictures of the ovarian tumour. However, the current methods can’t give clinicians detailed insight into patients’ likely overall outcomes or on the likely effect of a therapeutic intervention.