New Tech Has its AI on Brain Tumors

A collaboration across 29 research and healthcare agencies is putting together the world’s largest brain tumor dataset to answer the question: could artificial intelligence (AI) detect brain tumors better than doctors?

The project, led by Intel and Penn Medicine has received $1.2 million in grant funding over 3 years from the National Institutes of Health (NIH). Diagnostic technologies driven by AI and machine learning have already proven to themselves clinically in the detection of skin, breast and lung cancers. The key to establishing a robust diagnostic platform with minimal false positives or false negatives is to feed AI enough validated data for it to teach itself the difference between malignant and benign tissues.

Patient data, however, is extremely sensitive and subject to stringent privacy and security measures — making it a challenge for developers to access sufficiently large and robust datasets. To address this, the team is using a method known as federated learning, which uses encrypted data transfer and decentralized servers to securely channell patient data from participating centers.

Over 23,000 adults and 3,500 children in the United States will be diagnosed with a brain tumor this year. These masses of abnormal cells can be either cancerous or benign in nature, but both can cause severe neurological conditions…