Artificial Intelligence in Healthcare

Running head: ARTIFICIAL INTELLIGENCE IN HEALTHCARE
ARTIFICIAL INTELLIGENCE IN HEALTHCARE
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ARTIFICIAL INTELLIGENCE IN HEALTHCARE1
Artificial Intelligence (AI) is one of the significant contemporary issues in the field of
healthcare and is likely to decline the current health care system by 2020 (Maddox, Rumsfeld
& Payne, 2019). This paper shall elaborate on discussing about how AI is helping in the
development and advancement of the health care industry.
For improving the healthcare industry, artificial intelligence (AI) in the field of health
care is indeed a good idea as it can improve the communication of patients with the
healthcare professionals. Employees can function their best when they are capable of
practicing at peak performance. It is highly efficient of enhancing the capacity of processing
and storing huge amounts of data in intelligent way and translating information into the
functional tools (Wong & Bressler, 2016). It creates some intelligent computer systems,
which perform the tasks without receiving any instructions from the human beings. However,
sometimes, during the implementation of any technology or software, because of shortage of
knowledge, human beings do wrong and this adversely impact the equipment or the system.
In the same way, implementation of AI also highly enhance the care delivery but sometime,
can also be significant disruptive to the healthcare teams or providers (Vogenberg & Santilli,
2018).
In the healthcare industry, artificial intelligence is benefitting in many ways. The ever
increased availability and accessibility of the data along with the recent developments in AI
have presented some unprecedented chances and opportunities in the healthcare industry and
with the same, some major challenges for the regulators, patients, providers and developers.
According to Jiang et al. (2017) the main aim of AI is mimicking the human cognitive
functions. It is also claimed to be improving the human diagnosis system as the AI equipped
product has the potential of sifting through the disease data, medical records, clinical studies
as well as the health records of the patients too (Hamet & Tremblay, 2017).