Data-driven machine learning: A new approach to process and utilize biomedical data

With new diseases like Covid-19 and preexisting challenges like the shortage of skilled personnel, the need for new advancements in healthcare is acutely felt. This also includes the development of precise and accurate diagnostic tools to ease the pressure on the medical personnel, simultaneously enhancing efficiency. Machine Learning (ML) and Artificial Intelligence (AI) have emerged as promising solutions, and are being explored extensively. Their core concept, Artificial Neural Networking (ANN), is a banal yet faithful replica of the natural brain, making complex computing and “learning” possible. Being a gold mine of biomedical data, the healthcare sector serves as an invaluable resource for the development of such tools. However, there are numerous hurdles along the path to the realization of the same. This chapter explores the development of ANN-based diagnostic tools, focusing more on the aforementioned challenges. A brief overview of the current scenarios and future prospects of Machine Learning in Biomedicine has also been discussed.