Potential Integration of Artificial Intelligence and Biomedical Research Applications: Inevitable Disruptive Technologies for Prospective Healthcare

2.0 Literature Survey

AI seems more feasible than ever due to advancements in computing and processing power, coupled with hardware modernizations. The most significant AI breakthroughs of recent years can be attributed to machine learning. Instead of giving AI a fixed set of directions, AI models for healthcare applications is trained using large data sets to overcome the bias in outcomes. Increasing data generation from healthcare has led to potential improvements in accountability, quality, efficiency, and innovation. A great deal of research and innovation is conducted within the healthcare industry and hospital workflows. This is done with the goal of improving patient safety, reducing physician stress levels, and increasing the overall state of healthcare.

Gene technology, based on bioinformatics, offers enormous benefits for disease prevention and health care. The field of medical informatics today includes the concept of linking information sources through information and communication technology, enabling medical personnel to access information from a distance regardless of whether it comes from a patient's body or from an electronic archive (Snyder et al. 2011).