Computer Assisted Medical Decision Making
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2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)
The conference will provide an international forum for discussing the latest developments in the field of computational medicine, biomedical informatics and related fields.
Theoretical and practical aspects of machine learning (ML) algorithms and systems, ML systems involving applications in medicine, biology, industry, manufacturing, security, education, virtual environments, game playing, problem solving and energy.
2012 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
BIBM 2012 solicits high-quality original research papers (including significant work-in-progress) in any aspect of bioinformatics, biomedicine and healthcare informatics. New computational techniques and methods in machine learning; data mining; text analysis; pattern recognition; knowledge representation; databases; data modeling; combinatorics; stochastic modeling; string and graph algorithms; linguistic methods; robotics; constraint satisfaction; data visualization; parallel computation; data integration
Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.
The most highly-cited general interest journal in electrical engineering and computer science, the Proceedings is the best way to stay informed on an exemplary range of topics. This journal also holds the distinction of having the longest useful archival life of any EE or computer related journal in the world! Since 1913, the Proceedings of the IEEE has been the ...
Kwiatkowska, M.; McMillan, L. Fuzzy Systems (FUZZ), 2010 IEEE International Conference on, 2010
Computer-based support for medical decision making has been a subject of many research projects since the earliest days of computers. Although the early expert systems promised to automate medical diagnosis, very few systems were actually utilized in clinical settings. In the last twenty years, the intent to use computers to replace or simulate medical experts has changed to a less ...
Sang-Chul Lee; Bajcsy, P. Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on, 2007
This paper addresses the problem of understanding preservation and reconstruction requirements for computer- aided medical decision-making. With an increasing number of computer-aided decisions having a large impact on our society, the motivation for our work is not only to document these decision processes semi-automatically but also to understand the preservation cost and related computational requirements. Our objective is to support ...
Soo-Yeon Ji; Huynh, T.; van Najarian, K. Bioinformatics and Biomedicine, 2007. BIBM 2007. IEEE International Conference on, 2007
Traumatic pelvic injury is one of the life-threatening injuries because it is often associated with serious hemorrhage. Therefore, it is necessary to provide immediate medical treatments to the pelvic injury patients. But it is often difficult to make a decision because of a lot of similar cases existed. To help this problem, there are several medical applications designed to provide ...
Hudson, D.L.; Cohen, M.E. Computer Science and Information Engineering, 2009 WRI World Congress on, 2009
Traditional medical decision support systems have not met with widespread use in clinical practice. Issues that have prevented clinical adoption include narrow domain focus, models which are not sufficiently deep, and lack of trust in the system's reliability. While the methodologies may be sound, the acquisition of sufficient medical domain knowledge is often the drawback. In this work, basic methodologies ...
Wenan Chen; Smith, R.; Vasilache, S.; Najarian, K.; Ward, K.; Cockrell, C.; Ha, J. Bioinformatics and Biomedicine, 2009. BIBM '09. IEEE International Conference on, 2009
Traumatic pelvic injuries are complex and difficult to treat, due to the high risk of complications. Prompt and accurate medical treatment is therefore vital. Computer-aided decision-making systems can assist physicians in this task, but none of those proposed so far incorporate features extracted from medical images. The study in this paper uses demographic information, standard medical measurements, and features extracted ...
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