ABSTRACT
In the context of the rapid development of big data in the healthcare field, deep learning (DL), as a machine learning algorithm that provides a more flexible solution for image and speech recognition as well as natural language processing, has the ability to extract important information from medical data into valuable knowledge and it has received unprecedented attention in many real-world tasks. This paper briefly introduces common network structure of deep learning and its latest research progress in the field of medical laboratory. In addition, this review also exploreed some of the inherent challenges and prospective research directions about deep learning that affecting in the medical laboratory.
ABSTRACT
In the context of the rapid development of big data in the healthcare field, deep learning (DL), as a machine learning algorithm that provides a more flexible solution for image and speech recognition as well as natural language processing, has the ability to extract important information from medical data into valuable knowledge and it has received unprecedented attention in many real-world tasks. This paper briefly introduces common network structure of deep learning and its latest research progress in the field of medical laboratory. In addition, this review also exploreed some of the inherent challenges and prospective research directions about deep learning that affecting in the medical laboratory.