3 Common Challenges That Deep Learning Faces In Medical Imaging

Medical Imaging is one of the popular fields where the researchers are widely exploring deep learning. But the research may not translate easily into a practical or production-ready tech. In an engaging session by Abdul Jilani at the Computer Vision Developer Conference 2020, Abdul Jilani who is the lead data scientist at DataRobot explained the various challenges that applied machine learning face and how these can be overcome in real-time environments. "Building good training datasets and the wrong practices which lead to data leakage were the most commonly faced challenges that I investigated in a famous COVID X-rays prediction paper," he said. He further shared examples where Google's medical AI was super accurate in the lab, but the real-life story turned out to be very different, as it failed to give results at all when applied to real-life situations.