Abstract
Artificial intelligence (AI) is referred to as machines that can mimic human
cognitive functions. It usually engages various digital methods starting from computer
programming to deep learning, thus making use of the enormous structured and
nonstructured healthcare data. Artificial intelligence is gradually making a change in
medical practice by using sophisticated algorithms, assisting clinicians to mitigate
diagnostic and therapeutic errors and also using data intensive analysis for early
diagnosis of various diseases.
The chapter provides us an insight into the relationship between artificial intelligence
and healthcare, origin of artificial intelligence, different categories of artificial
intelligence and its applications in our healthcare system, various diseases for screening
as well as prognostic evaluation and eventually the issues pertaining to the
implementation of AI in medical devices.
The main focus is on the two major categories of AI which includes machine learning
and natural language processing. The former analyses the structured data such as
genetic or electrophysiological data while the latter deals with unstructured data such
as medical notes. In medical practice deep learning is mainly used to explore more
complex data. Cardiovascular health, neurological deficits and cancer are the most
challenging topics in AI.
AI technologies have created a stir in medical research yet it is facing various hurdles
in the form of regulations and data exchange. Thus, ethical and legal concerns need to
be addressed before the deployment of AI in the market.