• DocumentCode
    3736517
  • Title

    Intelligent decision systems in Medicine ? A short survey on medical diagnosis and patient management

  • Author

    Florin Gorunescu

  • Author_Institution
    Chair of Mathematics, Biostatistics and Informatics, University of Medicine and Pharmacy of Craiova, Craiova, Romania
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    The nowadays extensive use of computers in Medicine is remarkably widespread and covers almost all branches of the healthcare and biomedicine. Since the beginning of the computers rise, many scientists and doctors put their hopes in the aid that computers could provide in the medical decision-making based on their ability of storing and processing potential useful information/knowledge. Artificial Intelligence in Medicine has become a very important field in computer-aided medical research, covering various fields (e.g. automated diagnosis and therapy recommendation, image recognition and interpretation, patient management, tele-medicine/tele-health, etc.). A simple PubMed® search regarding the terms "Artificial Intelligence" and "Medicine" displays more than 2000 results, proving thus the huge interest in this field. The present paper presents a short review of some current Machine Learning algorithms (neural networks, genetic algorithms, support vector machines, Bayesian decision, k-nearest neighbor, etc.) used for automated diagnosis of different major diseases, such as breast, pancreatic and lung cancer, heart attacks, diabetes. Moreover, it also focuses on the intelligent patient management through Operations Research and Machine Learning techniques.
  • Keywords
    "Medical diagnostic imaging","Medical services","Artificial intelligence","Design automation","Computers","Solid modeling"
  • Publisher
    ieee
  • Conference_Titel
    E-Health and Bioengineering Conference (EHB), 2015
  • Print_ISBN
    978-1-4673-7544-3
  • Type

    conf

  • DOI
    10.1109/EHB.2015.7391552
  • Filename
    7391552