AI algorithm better at spotting cancerous nodules than other methods
New AI ‘can accurately spot cancer’: Algorithm is better at identifying cancerous nodules than existing methods, study claims
- The tool can spot whether abnormal growths found on CT scans are cancerous
- The algorithm performs more efficiently and effectively than current methods
A new artificial intelligence tool can accurately identify cancer in a development doctors and scientists said could speed up diagnosis of the disease.
The algorithm performs more effectively than current methods, according to a study.
It can identify whether abnormal growths found on CT scans are cancerous.
The AI tool, designed by experts at the Royal Marsden NHS foundation trust, the Institute of Cancer Research, London, and Imperial College London, could fast-track patients to treatment.
Cancer causes around 10 million deaths per year – nearly one in six deaths across the globe, according to the World Health Organization.
A new artificial intelligence tool can accurately identify cancer in a development doctors and scientists said could speed up diagnosis of the disease. [File image]
Dr Benjamin Hunter, a clinical oncology registrar at the Royal Marsden, said: ‘In the future, we hope it will improve early detection and potentially make cancer treatment more successful by highlighting high-risk patients and fast-tracking them to earlier intervention.’
The team used CT scans of about 500 patients with large lung nodules to develop an AI algorithm using radiomics, according to a report by The Guardian.
The technique can extract important information from medical images not easily spotted by the human eye.
The model was then tested to determine if it could accurately identify cancerous nodules.
The study used a measure called area under the curve (AUC) to see how effective the model was at anticipating cancer.
The algorithm performs more efficiently and effectively than current methods, according to a study. [File image]
According to The Guardian, An AUC of 1 indicates a perfect model, while 0.5 would be expected if the model was randomly guessing.
READ MORE: Artificial intelligence develops cancer treatment in just 30 days – and predicts how long patients have to live by reading doctors’ notes
The results showed the AI model could spot each nodule’s risk of cancer with an AUC of 0.87. The performance improved on the Brock score, a test used in clinic, which scored 0.67.
‘Through this work, we hope to push boundaries to speed up the detection of the disease using innovative technologies such as AI,’ said the Libra study’s chief investigator, Dr Richard Lee.
It comes after AI developed a treatment for an aggressive form of cancer in just 30 days and demonstrated it can predict a patient’s survival rate using doctors’ notes.
The breakthroughs were performed by separate systems, but show how the powerful technology’s uses go far beyond the generation of images and text.
University of Toronto researchers worked with Insilico Medicine to develop potential treatment for hepatocellular carcinoma (HCC) using an AI drug discovery platform called Pharma.
HCC is a form of liver cancer, but the AI discovered a previously unknown treatment pathway and designed a ‘novel hit molecule’ that could bind to that target.
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