A State-of-the-Art Survey of Deep Learning Techniques in Medical Pattern Analysis and IoT Intelligent Systems
الموضوعات :
Aref Safari
1
(Department of Computer Engineering, Islamic Azad University, Shahr-e-Qods Branch, Tehran, Iran)
الکلمات المفتاحية: deep learning, IoT, Medical Applications, Pattern Analysis,
ملخص المقالة :
Deep learning techniques have been concentrated on medical applications in recent years. The proposed methodologies are inadequate while medical applications' evolutionary and complex nature is changing quickly and becoming harder to recognize. This paper presents a systematic and detailed survey of the deep learning techniques in medical pattern analysis applications. In addition, it classifies deep learning techniques into two main categories: advanced machine learning and deep learning techniques. The main contributions of this paper are presenting a systematic and categorized overview of the current approaches to machine learning methodologies and exploring the structure of the effective methods in the medical pattern analysis based on deep learning techniques. At last, the advantages and disadvantages of deep learning techniques and their proficiency were discussed. This state-of-the-art survey helps researchers comprehend the deep learning field and allows specialists in intelligent medical research to do consequent examinations.
