IBM's IBM Predicts Breast Cancer A Year Before It Appears

The algorithm was trained on hundreds of thousands of non-personalized data on mammographic images and clinical

patient stories. The algorithm differs from similar neural networks in that it analyzes both sets of data, and not just one of them.

Resulting inAs a result, artificial intelligence is able to notice both obvious prerequisites for the occurrence of breast cancer and small details - for example, a lack of iron or problems in the thyroid gland.

The researchers improved the accuracy of the algorithm by adding data on biopsy, laboratory tests, registries of cancer patients, and more to its knowledge base.

Earlier it was reported that the next health crisis could arise from a huge amount of robot spam, which will not allow real patients to reach hospitals.