Before diving into code, let’s step back and consider why artificial intelligence is positioned to transform healthcare.
Much of AI’s momentum today can be attributed to the success of deep neural networks. This new era would not be possible without a perfect storm of the following four driving forces:
Deep learning has several advantages over traditional machine learning methods when it comes to performing supervised learning tasks:
i. Whereas traditional machine learning techniques rely on feature extraction by domain experts, deep learning algorithms learn high-level features from data on their own. This frees us from the requirement of domain understanding for feature extraction, thereby allowing us to create a smooth end-to-end pipeline that uses unstructured data such as images or text as input.
ii. Transfer learning enables us to benefit from the progress achieved by other researchers, thereby accelerating the development process.
iii. Deep learning achieves superior performance when…