Abstract
Contribution: This paper designs a learning and training platform that can systematically help radiologists learn automated medical image analysis technology. The platform can help radiologists master deep learning theories and medical applications such as the three-dimensional medical decision support system, and strengthen the teaching practice of deep learning related courses in hospitals, so as to help doctors better understand deep learning knowledge and improve the efficiency of auxiliary diagnosis. Background: In recent years, deep learning has been widely used in academia, industry, and medicine. An increasing number of companies are starting to recruit a large number of professionals in the field of deep learning. Increasing numbers of colleges and universities also offer courses related to deep learning to help radiologists learn automated medical image analysis techniques. For now, however, there is no practical training platform that can help radiologists learn automated medical image analysis systematically. Application Design: The platform proposes the basic learning, model combat, business application (BMR) concept, including the learning guidance system and the assessment training system, which constitutes a closed-loop learning guidance mode of “learning-assessment-training-learning”. Findings: The survey results show that most of radiologists met their learning expectations by using this platform. The platform can help radiologists master deep learning techniques quickly, comprehensively and firmly.
Highlights
In recent years, deep learning has developed rapidly in academia and industry, especially in the fields of speech recognition, image recognition and natural language processing [1] because deep learning can achieve precision that is unmatched by traditional methods
The BMR Medical Image Analysis Platform (BMRMIA) is a deep learning evaluation and training platform based on the concept of BMR, which aims to provide radiologists with learning guidance, online assessment, targeted reporting and personalized training services oriented toward deep learning technology
Based on the outcome-based engineering education (OBE) model [17–21], this paper proposes the concept of BMR pyramid-like learning guidance, which includes three kinds of abilities: basic learning (B), model combat (M) and radiological training application (R)
Summary
Deep learning has developed rapidly in academia and industry, especially in the fields of speech recognition, image recognition and natural language processing [1] because deep learning can achieve precision that is unmatched by traditional methods. In the study of information science and computer science radiologists in hospitals and universities, there is not a practical learning and training platform designed to help radiologists systematically learn automated medical image analysis technology. The platform includes a medical decision support system to allow radiologists to learn the application of deep learning. Through this system, radiologists can systematically grasp how deep learning is applied to the medical field. The platform aims to provide radiologists with learning guidance, online learning assessment, targeted reporting, and personalized training services for deep learning. Technology, helping learners to quickly, comprehensively and firmly master deep learning techniques and to help hospitals and universities narrow the gap between the output of deep learning talents and the standards of corporate talent demand
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