Science 2 min read

Researchers Develop Ovarian Cancer-Predicting AI System

Oncology doctor consults with patient | National Cancer Institute

Oncology doctor consults with patient | National Cancer Institute

A joint team of researchers from the Imperial College London and the University of Melbourne recently developed a cancer-predicting AI system to determine the survival rate of ovarian cancer patients.

The new technology reportedly predicts the prognosis of ovarian cancer patients more accurately than existing methods. Aside from that, it also determines the most effective treatment for a patient based on her prognosis.

To date, ovarian cancer is the sixth most common cancer in women. In the United Kingdom alone, there are 6,000 new cases of ovarian cancer every year.

With the new AI system’s predictive capabilities, clinicians can administer the best treatments to patients with epithelial ovarian cancer.

The Cancer-Predicting AI System

According to the study, the five-year survival rate of EOC is only 35 to 40 percent despite maximal treatment efforts. Therefore, stratification biomarkers are badly needed to make personalized treatments.

For their experiment, the researchers used their machine learning system known as TEXLab to create a non-invasive summary-statistic of the ovarian tumor based on four descriptors: structure, shape, size, and genetic makeup.

Based on the severity of a patient’s case, they receive a score called Radiomic Prognostic Vector (RPV) which ranges from mild to severe.

During the initial trial, the system identified 5 percent of the EOC patients with a median overall survival of fewer than two years. The prognosis made by the AI system was validated by two independent cohorts, further proving its capability to improve established prognostic methods.

“Artificial intelligence has the potential to transform the way healthcare is delivered and improve patient outcomes,” Andrea Rockall, co-author of the study from Imperial College Healthcare NHS Trust, said in a press release.

“Our software is an example of this, and we hope that it can be used as a tool to help clinicians with how to best manage and treat patients with ovarian cancer.”

The team’s research study and results of the initial trial were published in the journal Nature Communications.

Read More: Personalized Vaccine For Ovarian Cancer Shows Promising Results

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