The need for information technologies is increasing in the provision of health services and the improvement of public health. It is inevitable to use artificial intelligence applications in healthcare services and management due to reasons such as increasing workload, insufficient health workforce, limitation of resources.

Artificial Intelligence emerged in the 1950s as a research area. Machine learning and deep learning models are used in the creation of artificial intelligence algorithms that consist of functions that aim to imitate human cognition. Perceived as the most transformative technology for the 21st century and the future, artificial intelligence has significant social and economic impacts. Big tech companies invest billions of dollars in artificial intelligence research.

The introduction of artificial intelligence into the field of health dates back to the 1970s and among the first artificial intelligence applications are MYCIN, CASNET and Internist-1 expert systems. With the increasing availability of health care data and supported the rapid progress of analytical techniques has brought about a paradigm shift in health care. Within the scope of health services, it has started to show itself in early diagnosis and treatment, medical decision making, medical imaging and drug development.

According to the data of the Organisation for Economic Co-operation and Development (OECD), it has been declared that 20% of health expenditures are wasted worldwide. Misdiagnosis of illness, insufficient care services, unnecessary tests and medical practices are the main reasons for this waste. It is thought that these reasons will be prevented by helping to make fast and effective decisions in the provision of health services by artificial intelligence studies. While artificial intelligence applications in the medical field are often used for clinicians to interpret radiological images quickly and accurately, it is aimed to accelerate the work flow for health systems and to minimize errors. At the same time, improving health by processing big data represents one of the most important goals. There are opinions that all healthcare professionals will use artificial intelligence technologies in the future and that a "high performance medicine" field will be created. Also in the documentation of data, in cost and quality management, in the rational use of capacities of health institutions, in the realization of remote preventive and complementary health services it is thought that it can also help health administrators.

A patient-oriented digital ecosystem has begun to be created with technological developments. Today, the existence of many biological databases open to the public and the ability to process these data play an important role in artificial intelligence studies. Cancer Genome Atlas, which contains information on cancer patients, and Drugbank, which contains drugs under development, approved or unapproved, are examples of these databases. Artificial intelligence applications are being developed in many areas such as, Artificial intelligence-supported surgeries with Da Vinci Surgical Robots, artificial intelligence-supported wearable devices, IBM Watson artificial intelligence-supported systems established and known as an aid in oncological diagnoses, cancer screening, especially breast cancer, systems that remind the medication times of geriatric patients, diagnosis of Alzheimer's disease,detecting Down syndrome through facial images, transcribing speech into text, making a psychiatric diagnosis using semantic analysis. The WeCureX project was developed by Tütün et al. As an artificial intelligence assistant application aimed at the analysis and diagnosis of mental disorders, and it was reported that it could reach the diagnosis with 97% consistency through the answers given by the clients to the questions. In a hospital in Sanliurfa, over 600 thousand unnecessary tests were prevented in 2 years with 5 algorithms developed to prevent unnecessary laboratory requests. It has been stated that if these algorithms are applied in all public hospitals throughout the country, it is possible to save 200 million lira annually.

There are also studies conducted for the follow-up of epidemic diseases. During the bird flu epidemic in Canada, a Twitter-based data analysis was developed and its potential to represent the epidemic was examined. It has successfully identified 75% of the epidemic notifications in the world. Again, during the COVID-19 outbreak, Google published the "COVID - 19 Community Mobility Report" for Turkey in April 2020 with the data it obtained through a very simple artificial intelligence application. In this report, it was determined how much the mobility decreased in workplaces, markets and open areas compared to the pre-epidemic period. With the development of such systems across the country, it is possible to monitor how well individuals comply with social distance measures during the epidemic period.

It is thought that, with these applications developed and continued to be developed with artificial intelligence, the pressure on healthcare personnel will be reduced, costs will be reduced, the process will be managed more quickly and effectively, and ultimately will help patients' lives improve. In addition to the advantages of artificial intelligence technologies that are starting to make big waves in healthcare, they continue to create discussions about whether they will replace doctors in the future. Concerns also arise regarding ethical and legal issues. An international meeting was held by the World Health Organization in October 2019 to ensure the development of ethical and managerial guidance for the design and implementation of artificial intelligence in global health. Because of the international nature of these technologies, security problems related to the access and sharing of data produced or used are also pointed out, but worldwide studies are being developed on this subject.