Research shows AI capable of treating brain tumors faster and more accurately

According to a study recently released by Harvard Medical School, a new intelligence tool artificial is being developed to help neurosurgeons in the treatment of brain tumors, specifically the gliomas.

Gliomas are common brain tumors in cancer patients. Neuroscience researchers have been working hard for decades to better understand this disease.

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Gliomas can vary in aggressiveness. There is a particularly aggressive type who was responsible for the death of Beau Biden, son of former US Vice President Joe Biden and Arizona Senator John McCain.

According to one of the researchers involved in the Harvard Medical School study, Kun-Hsing Yu, different types of gliomas require different surgical approaches.

Artificial intelligence will help in the diagnosis of the disease

When removing a glioma, it is crucial that neurosurgeons have access to detailed information to ensure patient safety and prevent damage to adjacent brain tissue. However, this information is often only available when the patient is already on the operating table.

During surgery on brain cancer patients, doctors often send a tissue sample to the pathology lab to get immediate real-time feedback, according to Yu.

Pathological analysis allows doctors to confirm that they are removing the correct tissue and to identify the specific type of cancer the patient has.

In advanced medical facilities, pathological analysis of a brain tissue sample can be completed in approximately 10 to 15 minutes while the patient is still on the operating table with the open skull.

Yu emphasized that this process is not foolproof, as pathologists have to stop their activities to prioritize samples from ongoing surgeries.

This scenario can be stressful and sometimes result in suboptimal samples, leading to occasional misdiagnosis due to the fast-paced nature of the process.

Recognition of these limitations highlights the importance of improving pathological analysis techniques and seeking solutions that minimize errors during brain tumor removal surgery.

The introduction of artificial intelligence tools can provide additional support to pathologists and neurosurgeons, helping to improve diagnostic accuracy and ensuring the best possible care for patients.

The team led by Yu made a significant discovery by applying machine learning techniques. An offshoot of artificial intelligence, where technology learns patterns without explicit instructions from a programmer, this application has made glioma analysis faster and more accurate.

This technology has the potential to reduce the time patients need to spend in the operating room.

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