Comparison and Performance Evaluation of Deep Learning and its Impact on Medical Engineering and Healthcare Management - Muthukumar Subramanian, Dhruva Sreenivasa Chakravarthi, D. Jeyakumar, Mohamed Suhail. M, Dhiraj Kapila, Sushma Jaiswal (Drugs and Cell Therapies in Hematology, 2021)
Over recent decades, there has been a growing interest in artificial intelligence in the healthcare research field, with the goal of providing large data processing and augmenting judgement capabilities. An important factor in this is the tremendous effect of deep learning on the use of complicated healthcare large data, which is a major motivation for this. Despite the fact that deep learning is a strong analytical method for the massive information included in electronic health records (EHRs), there are certain restrictions that may make the use of deep learning in specific healthcare applications substandard. Throughout this article, we provide a short review of the limits of deep learning, which are demonstrated via example studies that have been conducted throughout time with the goal of encouraging the adoption of alternate analytical techniques for healthcare.