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Tag: medical imaging

What Digital Pathology can learn from Radiology

Radiology is ahead of the curve because they’ve had CAD (Computer Aided Detection) for about 20 years. Radiology as a field has therefore had experience of introducing and integrating AI algorithms.

In my previous post, I talked about high-level cross imaging modalities. Here, I will discuss three challenges specific to pathology. I also work with Radiology imaging, and I think that comparisons between the two can help see how pathology might develop in the future.

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Four challenges in developing AI algorithms for medical imaging

Unsurprisingly, there is a lot of hype surrounding AI. Available deep learning packages make it so easy to create models and so we can expect lots of them to emerge. Anyone able to access sufficiently labelled data can start building models.

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The promise of AI in medical imaging: improving medical practice

In our lab of Quantitative Imaging and Artificial Intelligence, we’re developing AI applications in a variety of areas, such as radiology and pathology. The goal is to develop applications that meet unmet medical needs, particularly in relation to precision medicine and clinical prediction.

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