DERİN ÖĞRENME VE SAĞLIK ALANINDAKİ UYGULAMALARI. - KELEŞ, Ali (Electronic Turkish Studies)
Artificial Intelligence (AI) causes new transformations in the medical world. Today, AI can help doctors diagnose faster, more accurately, predict disease risk to prevent diseases beforehand, and help researchers understand how genetic variations lead to disease. Although AI has existed for years, it has created an explosion in recent years with Deep Learning (DL) which is a new form of learning. Thanks to this new AI technique, self-driving tools, super-human image recognition and life-changing, even life-saving developments have become possible. The DL helps researchers analyze medical data for disease treatment, increases physicians' ability to analyze medical images, and contributes significantly to the future of the personalized drug. Basically three trends lead the DL revolution. These are more powerful GPUs (Graphics Processing Unit), advanced neural network algorithms that model the human brain, and access data from the Internet. This study focuses on the emerging deep learning in the field of machine learning, one of the AI technologies. What deep learning is, and its importance, emphasizes the most well-known DL architectures. Deep learning has serious potential to change and improve many things in our lives, and researches are supported in every aspect by making serious investments. However, it's potential and importance in the field of health touching human life leads to great improvements. This study demonstrates the practices in the field of health and international studies of valuable scientists in this field. As a result, deep learning technology with such a great potential has much to add to the health practices in our country. What is happening in the world in this field should be followed closely. Health practices that change and protect human life can be developed by our valuable researchers with the support of the state and the cooperation of health institutions and these applications can be successfully integrated into the health system. It is foreseen that this research paper presented in this context will contribute significantly to the field.