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.