Use of Artificial Intelligence in the Healthcare Sector

Artificial intelligence (AI) has profound effects not only on the medical sector but also on many other sectors. AI, whose theoretical foundations were laid in the 1950s, has since developed into different AI subfields. Recently, two prominent subfields within the scope of AI have been machine learning (ML) and deep learning (DL) techniques. ML is focused on analyzing existing data to make predictions, and DL employs neural networks to mimic the functioning of the human brain. Today, observing many projects and even daily applications related to the use of AI in different areas such as medical imaging, diagnosis, drug development, and personalized treatment plans is possible in the health sector. For example, in the field of radiology, making earlier and more precise diagnoses using AI to increase the speed and accuracy of medical image analysis has become possible. Robotic surgery platforms, such as the Da Vinci Surgical System, have begun to integrate AI to automate tasks and improve surgical safety. With smartphones, wearable technologies, and Internet of Things applications, AI-powered healthcare solutions are becoming more accessible and effective. This paper aims to provide a brief overview of AI, examine its contributions and real-world applications in healthcare, assess its impact on medical education, and discuss the ethical challenges of its integration into the medical field. By providing insights into the potential of AI, this study aims to provide healthcare professionals a comprehensive perspective on the role of AI in modern medicine.

Keywords: Artificial intelligence; Artificial intelligence in medicine; Deep learning; Machine learning