Chronic diseases are the leading causes of death and disability worldwide. By 2020, it is expected to increase to 73% of all deaths and 60% of global burden of disease associated with chronic diseases. For all these reasons, early diagnosis and treatment of chronic diseases is very important. Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning is the development of computer programs that can access data and use it to learn for themselves. The learning process starts by searching for patterns in the examples, experiences, or observations. It will make faster and better decisions in the future based on all these. The primary purpose in machine learning is to allow computers to learn automatically without human help and affect. Considering all the reasons above, this chapter finds the most appropriate artificial intelligence technique for the early detection of chronic diseases.
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We all know that the world population and average life expectancy are increasing. As a result of the increasing population and increasing life expectancy, the annual applications to the health sector are increasing rapidly. With these increasing applications, the examination times of physicians are shortened. Malpractice (medical malpractice) is defined as the harm caused by the physician's failure to perform standard practice, lack of skills or failure to treat the patient (Koc, 2014). Reduced examination times bring the risk of malpractice. For all these reasons, physicians should diagnose patients who come to their clinic in a short time.
Healthcare is defined as studies for health protection, treatment and rehabilitation of diseases. The aim of the health service is to increase, improve and maintain the health level of society and individuals. Healthcare services are divided into 3 classes: preventive health services, therapeutic health services and rehabilitative health services (Rakel & Rakel, n.d.). Also, therapeutic health services are divided into three groups: primary health care services, secondary health care services and tertiary health care services (AYGN et al., 2016). Health institutions provide all of the preventive, therapeutic and rehabilitative health services to the individual or families. However, the distribution of all these health services varies. Preventive health services come to the fore in primary health care services. In addition, the primary healthcare, which is first step of healthcare services, is great importance in the early diagnosis and follow-up of the diseases. Because primary healthcare cares about people rather than treatment certain diseases (Rakel & Rakel, n.d.).
Chronic diseases are affecting more and more people with increasing life span. Chronic diseases are the leading causes of death and disability worldwide. Chronic disease rates accelerate globally, progress in each region and affect all socioeconomic classes(“WHO | Projections of mortality and causes of death, 2016 to 2060,” 2018). Early diagnosis and treatment of chronic diseases is very important. Family physicians in primary care examine their patients regularly and keep all information digitally thanks to the patient follow-up programs they use today. In fact, these regularly recorded data provide an unprecedented opportunity for people to be diagnosed early (Rakel & Rakel, n.d.).
Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Using the machine learning technique, we can conduct research across chronic diseases and healthy individuals based on the currently selected medical data sets. Using some machine learning techniques, the prediction of chronic disease can be simplified using a variety of features to determine whether a person is at risk for chronic disease. It also takes less time for early diagnosis and treatment of diseases (“What is artificial intelligence?,” n.d.).
Considering all the reasons above, the aim of this chapter is to find the most appropriate artificial intelligence technique for the early detection of chronic diseases by using the data set, which was used in a study conducted on the staff working on a university campus.