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With the probable incidence of ovarian cancer in the space of 55% within 15 years, researchers have created artificial intelligence (AI) software to best treat ovarian cancer, opening thus the way to personalized medicine and effective relief. study says.
Mathematical software TEXLab also predicts which treatment would be most effective for patients in the World Ovarian Cancer Coalition, predicting that deaths will probably increase by 67% by 2035 because of this cancer.
This technology can be used to identify patients unlikely to respond to standard treatments and offer alternatives, as ovarian cancer is the sixth most common cancer among British women who usually occur after menopause or those with a family history of the disease.
Early detection of the disease could improve survival rates, noted the study.
"The long-term survival rate of patients with advanced ovarian cancer is poor despite advances in treatment. There is an urgent need for new methods, "said lead author Eric Aboagye, a professor at Imperial College London.
For the study, the researchers used the software to identify the aggressiveness of the tumors in the scans and tissue samples of 364 women with ovarian cancer.
The patients then received a score called radiological prognosis vector (RPV) indicating the severity of the disease, ranging from mild to severe.
The results, published in Nature Communications, showed that the software was up to four times more accurate in predicting ovarian cancer deaths than standard methods.
In addition, the results showed that five percent of patients with high scores of RPV had a survival rate of less than two years.
High VPR was also badociated with resistance to chemotherapy and poor surgical results, suggesting that RPV can be used as a potential bio-marker to predict how patients would respond to treatment.
"Our technology is able to provide clinicians with more detailed and accurate information about the likely response of patients to different treatments, which could enable them to make better and more targeted treatment decisions," said Aboagye.
At present, doctors are diagnosing ovarian cancer in different ways, including a blood test followed by a scanner using X-rays and a computer to create detailed images. of the ovarian tumor.
This helps clinicians know how far the disease has spread and determines the type of treatment that patients receive, such as surgery and chemotherapy.
However, the badyzes can not provide clinicians with detailed information about the likely overall outcome of patients or the likely effects of a therapeutic intervention.
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First published: February 16, 2019 13:36 IST
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