Medical Information Forensics System Based on Convolutional Neural Network with Pattern Finding Prior
Hospital Information System HIS is an indispensable technical support environment and infrastructure for modern hospitals. It reflects the comprehensive management of a modern hospital. Many hospitals have established local networks and implemented some subsystems, such as inpatient
toll collection systems and drug management systems, which have yielded some success. Medical information forensics is a comprehensive process of using scientific methods to collect network data, identify intrusion, analyze data, store data, determine the reason of intrusion tp enhance security
equipment and trigger alarm procedures. In this paper, we study the concepts and techniques of medical information forensics, and discuss the definition, classification, sources and characteristics of medical information forensics. The deep learning model and the data analytic framework are
combined to provide the comprehensive analysis of the research. The technique novelty is validated through the experiment. The simulation compared with the other state-of-the-art methodologies proves the efficiency of the method.
Keywords: Convolution Neural Network; Deep Learning; Forensics System; Medical Imaging; Medical Information; Pattern Recognition
Document Type: Research Article
Affiliations: 1: College of Mechanical Science and Engineering, Jilin University, Changchun, 130025, P. R. China 2: School of Mechanical Engineering, Tianjin University of Technology, No. 391, Binshuixidao, Xiqing District, Tianjin, 300384, China 3: The First Hospital of Jilin University, Changchun, Jilin Province, 130000, China
Publication date: 01 May 2020
- Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Ingenta Connect is not responsible for the content or availability of external websites
- Access Key
- Free content
- Partial Free content
- New content
- Open access content
- Partial Open access content
- Subscribed content
- Partial Subscribed content
- Free trial content