How to de-identify medical image data

One of the dominant methods in automatic image-based diagnostics is Deep Learning. This type of algorithm must be fed large volumes of medical data to learn how to spot suspicious abnormalities on medical images, such as a tumor or a fracture. The more data you feed into the algorithm, the more accurate the algorithm gets. The question is: how to deidentify medical data before you feed it to Deep Learning algorithms?

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Preventing Medical Data Biases

The healthcare of the future being created as we speak -- but if we're not careful it will leave some populations behind. Find out what Segmed is doing to help empower medical advancements that will work for everyone.

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Cailin Hardell
Segmed: Your Long Term Data Partner

Medical AI is often hailed as the future of medicine and will improve diagnostics, increase quality of patient care, enable further-sighted prediction of diseases, boost affordability of healthcare, and make healthcare available to many more people across the world. These are ambitious and admirable goals, and Segmed wants to enable this reality to improve the lives of millions seeking and requiring medical support.

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Jacqueline Sim