Case Study A 2 017 study out of the Massachusetts General Hospital and MIT showed that an artificial intelligence (AI) system was equal or better than radiologists at reading mammograms for high risk cancer lesions needing surgery. A year earlier, and reported by the Journal of the American Medical Association, Google showed that computers are similar to ophthalmologists at examining retinal images of diabetics. And recently, computer-controlled robots performed intestinal surgery successfully on a pig. While the robot took longer than a human, its sutures were much better more precise and uniform with fewer chances for breakage, leakage, and infection. Tech boosters believe that AI will lead to more evidence-based care, more personalized care, and fewer errors. Of course, improving diagnostic and therapeutic outcomes are laudable goals. But AI is only as good as the humans programming it and the system in which it operates...
DeepLearning Frameworks That Techies should learn in 2022. Deep learning framework s help data scientists and ML developers in various critical tasks. As of today, both predictive analytics and machine learning are deeply integrated into business operations and have proven to be quite crucial. Integrating this advanced branch of ML can enhance efficiency and accuracy for the task-at-hand when it is trained with vast amounts of big data. In this video, we will explore the top deep learning frameworks that techies should learn this year Tensor Flow : The Javascript-based open-source learning platform has a wide range of tools to enable model deployment on different types of devices. While the core tools facilitate model deployment on browsers, the lite version is well-suited for mobiles and embedded devices. Keras : It is an open-source framework that can run on top of Tensorflow, Theano, Microsoft Cognitive Toolkit, and Plaid ML. Keras framework ...
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