Artificial Intelligence for Healthcare: A Structured Review

Abstract

The study of artificial intelligence (AI) spans a wide range of academic disciplines and has its roots in many different fields,
including logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering.
The modern science of artificial intelligence was born with a modest summer workshop held at Dartmouth College in 1956.
Since then, AI applications enabled by machine learning (ML), an AI subdiscipline, include Internet searches, e-commerce
websites, products and service recommender systems, picture and speech recognition, sensor technologies, robotic devices,
and cognitive decision support systems (DSSs). Similar to how earlier general-purpose technologies like steam engines,
railroads, electricity, electronics, and the Internet have changed society and the economy globally, it is projected that as more
applications are integrated into daily life, AI will have a revolutionary impact on these systems. Future workplaces may use
novel AI applications, which raises significant concerns for worker safety and health. This essay examines the history of AI, the
usage of ML techniques, and new AI applications that are being integrated into physical things like sensor technologies, robotic
devices, or intelligent DSSs. The management of human-machine interactions and some of the potential job displacement
caused by automation caused by the deployment of AI technologies are also reviewed. A proactive rather than reactive approach
to occupational research and practice will result from exercising strategic foresight regarding AI workplace applications. It
will be easier to reduce the negative consequences of AI on worker safety, health, and well-being if workers are aware of the
opportunities and difficulties that AI presents for the future of work.