MEDICAL INFORMATICS IV
APPLICATIONS OF DEEP LEARNING METHODS IN THE FIELD OF HEALTH: PREDICTION OF DIABETIC RETINOPATHY
Yayıncı:
İstanbul Üniversitesi Yayınları
For many years, medical imaging techniques have been used as an important tool in the diagnosis and treatment of diseases. Deep learning methods, which are a sub-branch of machine learning, play an important role in the early diagnosis of diseases, in the rapid interpretation of images obtained from medical imaging tools, in reducing the workload of medical professionals, providing insights in the disagreements to be experienced at the point of decision-making, and making the right decisions. In the management, interpretation and analysis of heterogeneous big data obtained from different sources in the field of health, deep learning methods are used today as a more powerful tool than traditional methods in the field of image processing. In recent years, deep learning methods have increasingly become the focus in the analysis of big data obtained in image processing in disease detection. In this study, the use of deep learning methods in the field of image processing in the early diagnosis of diseases has been examined. In addition, deep learning models were used in the early diagnosis of diabetic retinopathy in the study. The image data obtained from APTOS 2019 Blindness Detection was used in the diagnosis of diabetic retinopathy disease. According to the results obtained, it was concluded that deep learning models are an important method in image processing, and its use in the early diagnosis of diabetic retinopathy will be a serious tool for medical professionals
