Artificial Intelligence Will Be an Inseparable Part of Medicine in the Future

Istanbul Gelisim University (IGU) Health Services Vocational School (SHMYO) Lect. Sibel Haklı stated that the term Artificial Intelligence was coined by John McCarthy during a conference on this subject in 1956, and the possibility that machines can imitate human behavior and actually think was brought up earlier by Alan Turing, who developed the Turing test to distinguish humans from machines. Since then, computational power has reached the point of instantaneous calculations and the ability to evaluate new data in real time based on previously evaluated data. Today, artificial intelligence is integrated into our daily lives in many forms such as personal assistants (Siri, Alexa, Google assistant, etc.), automated public transportation, aviation and computer games. More recently, artificial intelligence has begun to be incorporated into medicine to improve patient care by speeding up processes and achieving greater accuracy, paving the way for better healthcare overall. Artificial intelligence is a technology that is rapidly adopted in many industries to increase time efficiency and reduce cost at the same time. In medicine, this technology translates into better patient care, improved workflow through early detection and diagnosis, thereby reducing medical errors, reducing medical costs, as well as reducing morbidity and mortality. Artificial intelligence in medicine; It is divided into two subtypes, virtual and physical. The virtual part ranges from applications such as electronic health record systems to neural network-based guidance in treatment decisions. The physical part is about robots that help perform surgeries, smart prosthetics for the disabled, and aged care. Computers learn the art of diagnosing a patient with the technique of flowcharts and database approach. The flowchart-based approach involves the history-taking process, that is, a doctor asking a series of questions and then combining the presented symptom complex to arrive at a possible diagnosis. This requires feeding massive amounts of data into machine-based networks, given the wide variety of symptoms and disease processes encountered in routine medical practice. The results of this approach are limited because machines cannot observe and collect clues that can only be observed by a doctor during a patient encounter. The database approach is based on specific symptom groups or specific clinical