The classification of brain tumors – and thus the choice of optimal treatment options – can become more accurate and precise through the use of artificial intelligence in combination with physiological imaging. This is the result of an extensive study conducted by the Karl Landsteiner University for Health Sciences (KL Krems). Multiclass machine learning methods were used to analyze and classify brain tumors using physiological data from magnetic resonance imaging. The results were then compared with classifications made by human experts. Artificial intelligence was found to be superior in the areas of accuracy, precision and misclassification, among others, while professionals performed better in sensitivity and specificity. Brain tumors can be easily detected by magnetic resonance imaging (MRI), but their exact classification is difficult in this way.

A Chinese AI system diagnosed brain tumors and other conditions more accurately and faster than a team of top Chinese physicians, according to Xinhua. The AI, called BioMind, was developed by the Artificial Intelligence Research Centre for Neurological Disorders at Beijing Tiantan Hospital. The AI correctly diagnosed 87 percent of 225 cases in just 15 minutes, while a team of 15 senior physicians diagnosed 66-percent of the cases accurately. When it came to predicting cases of brain hematoma expansion, the AI won yet again: with correction predictions in 83 percent of cases, whereas doctors only achieved 63-percent. And that's not because the doctors were slacking.