New AI-powered Deep Learning Model Supports Medical Diagnostics

Deep learning is a type of artificial intelligence (AI) that is being researched to see how accurate it can be to diagnose some diseases faster. This type of AI uses algorithms to detect patterns based on a large amount of existing data. The machine or device learns from this, and then makes predictions based on what it learns. The problem is that medical data is highly regulated, making it more difficult to get the amount of data needed, at least initially. Privacy policies restrict the number of images and amounts of data available for learning. 

When less data is used, predictions are less reliable. The researchers on the project studied how to make AI learning more effective with less information. They train the algorithm with likely scenarios from medical experts though without all of the information provided. This ensures that there is enough data to detect the potential patterns to learn to identify the likely diagnoses. This is meant to help speed up the work of radiologists by giving them better tools. With faster, more accurate AI, it should give medical professionals more information to make better informed decisions.

One of the members of the original research team who made significant contributions died when Flight PS752 crashed. She was instrumental in working on the project. The team views the work as a way of also memorializing them.

If you’re interested in learning more about the potential of what deep learning can do, check out New AI-powered Deep learning Model Supports Medical Diagnostics.

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