Introduction & Background:
Artificial intelligence (AI) is the type of digital computer system that
parallels the way the human brain processes information. AI is organized
in a similar way that neurons in the brain are arranged, with their
multiple neural nodes, and so are referred to as Neural
Networks [1,2]. The rise of AI has led to the subsequent development
of artificial neural networks (ANN), which consist of a dependable
mathematical system that can interpret multifactorial
data [3,4,5]. These neurons are connected via multiple synapses and
send the data to each other back and forth, and by doing so, coming up
with the most probable answer. Making these multiple connections enables
computers to mimic cognitive functions such as the reasoning process to
identify the most probable answer to a problem. This complex algorithm
AI software is now utilized in medicine to analyze large amounts of
data, which can assist in disease prevention, diagnosing and monitoring
patients [2]. In recent years, there has been an enormous rise in
the global growth of artificial intelligence in healthcare systems.
According to statistics, expenditure on AI is expected to increase from
$2.1 billion to $36.1 billion by 2025.3 Artificial intelligence
requires training and collaboration between partners for it to become a
success in healthcare. One example is IBM Watson Health, a well-known AI
technology that has received appraisal from customers and is mostly used
for prescription information extraction from various drug databases and
medical journals [4].
Overall, AI can aid practitioners in decision-making and will help
clinicians to make more self-assured decisions, however, it is important
to keep in mind that it is not a substitute for clinical
experience [3]. The third leading cause of death in the US is
medical errors, and AI can potentially help reduce them, by improving
accuracy in interpretation, and decreasing the workload that can lead to
details being overlooked [5]. In this article, we introduce
different types of AI, their potential applications, as well as
associated research, benefits, and limitations, and the future of AI,
and how it can benefit the field of Obstetrics and Gynecology.