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AI Tool Tested in Belgium to Personalize Breast Cancer Treatment
(MENAFN) Four breast clinics in Belgium's Flanders region are piloting an artificial intelligence system built to help doctors determine the most effective treatment path for individual breast cancer patients, a Dutch-language broadcaster reported Friday.
Developed by RADar, the innovation hub of AZ Delta, the tool is designed to arm doctors with extra data at the point of diagnosis — potentially sharpening treatment decisions and helping patients avoid unnecessary surgery.
The system tries to forecast three things early on: how a patient will likely respond to chemotherapy, whether cancer has reached the lymph nodes under the arm, and the tumor's size.
"These are things we usually only find out later in the care trajectory today," said Barbara Bussels, coordinator of the breast clinic at AZ Delta. "If we already have that information at the time of diagnosis, it can help to better assess which treatment is most suitable for which patient," she added.
Philip Poortmans, a radiation oncologist at ZAS clinic, said the system can spot patterns doctors might miss when reviewing individual pieces of medical data in isolation. "Through this approach, artificial intelligence can recognize patterns that are difficult or even impossible to detect with the human eye," he said.
One target application: predicting whether cancer will spread to the armpit's lymph nodes. Sharper forecasts could let surgeons fine-tune — or in some cases skip entirely — procedures involving that area, lowering the risk of complications like lymphedema, pain and limited mobility.
The tool isn't yet guiding real treatment decisions. Since early June, specialists at the four hospitals have been testing it independently against historical patient records to gauge whether it can sharpen and personalize care recommendations. Promising models will then move into real-world clinical trials.
Bussels said that once the system earns European certification, it could eventually be rolled out to breast clinics across the continent.
Developed by RADar, the innovation hub of AZ Delta, the tool is designed to arm doctors with extra data at the point of diagnosis — potentially sharpening treatment decisions and helping patients avoid unnecessary surgery.
The system tries to forecast three things early on: how a patient will likely respond to chemotherapy, whether cancer has reached the lymph nodes under the arm, and the tumor's size.
"These are things we usually only find out later in the care trajectory today," said Barbara Bussels, coordinator of the breast clinic at AZ Delta. "If we already have that information at the time of diagnosis, it can help to better assess which treatment is most suitable for which patient," she added.
Philip Poortmans, a radiation oncologist at ZAS clinic, said the system can spot patterns doctors might miss when reviewing individual pieces of medical data in isolation. "Through this approach, artificial intelligence can recognize patterns that are difficult or even impossible to detect with the human eye," he said.
One target application: predicting whether cancer will spread to the armpit's lymph nodes. Sharper forecasts could let surgeons fine-tune — or in some cases skip entirely — procedures involving that area, lowering the risk of complications like lymphedema, pain and limited mobility.
The tool isn't yet guiding real treatment decisions. Since early June, specialists at the four hospitals have been testing it independently against historical patient records to gauge whether it can sharpen and personalize care recommendations. Promising models will then move into real-world clinical trials.
Bussels said that once the system earns European certification, it could eventually be rolled out to breast clinics across the continent.
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