The Role of Machine Learning in the Healthcare Sector: A Roadmap to the Potential Prospects

The role of machine learning in the health sector is significant in enhancing medical outcomes, reducing health care costs, and promoting medical research. However, numerous medical institutions are not presently employing ML technologies in their day-to-day work. This is partly because many health care practitioners lack the ML knowledge required to develop prosperous solutions, employ them in production, and utilise them in the medical workflow. Automated ML is a growing field that seeks to automate the selection, composition and parameterisation of ML models to achieve optimal execution in given scenarios. This study aims to investigate the potential prospects using current literature in the domain of ML in general and Automated ML, in particular, to assist healthcare practitioners in utilising ML models that are available “off-the-shelf” and do not require extensive knowledge of ML. This study reviews published papers providing code and targeting the research in ML from both perspectives, computer science and biomedical information science. In this regard, a review of 70 studies discovered that reducing the amount of time the use of these automated ML systems can assist in matching or improving human expertise in particular ML scenarios at small and medium datasets even though there is a significant work done in the domain of Automated ML for health care further work is required for the extensive adoption of ML in health care department.