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IBM technology detects breast cancer risk before it happens

With the new step in medical diagnosis, IBM has developed an artificial intelligence model which is capable of predicting malignant breast cancer within a year with an 87 percent accuracy rate (when the output from the machine is compared with expert radiologists.) In addition, the technology could correctly predict 77 percent of non-cancerous cases. The prediction methods uses both mammogram images and medical records in order to make the assessment, based on a data review of the medical evidence. This is the first application of AI to draw upon both images and data to make a prediction in relation to breast cancer.

At the heart of the deep neural network technology is an algorithm, which IBM technologists along with medical professionals (from Israel’s largest healthcare organizations) trained. The training of the artificial intelligence took place using anonymized mammography images which were linked to biomarkers (like patient reproductive history) together with clinical data. The training data-set consisted of 52,936 images from 13,234 women who underwent at least one mammogram between 2013 and 2017.

The aim of the medtech is not to replace the physician, but to act as a ‘second pair of eyes’, providing a backup in the event that something has been missed through conventional patient assessment. This could prove especially useful in areas with staff shortages where a second medical professional is not available to provide a second assessment.

An assessment of the technology has been published in the journal Radiology. The research paper is titled “Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms.”

In related news, IBM are applying artificial intelligence to catch Type 1 diabetes much earlier. IBM’s other health technology project could help identify patients at risk and help chart a course for tracking the condition. The predictive tool is a joint project between IBM and JDRF (formerly known as the Juvenile Diabetes Research Foundation).

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Written By

Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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