Self-Enforcing Networks (SEN) for the development of (medical) diagnosis systems | IEEE Conference Publication | IEEE Xplore

Self-Enforcing Networks (SEN) for the development of (medical) diagnosis systems

Publisher: IEEE

Abstract:

A Self-Enforcing Network, which is a self-organized neural network, is introduced to develop a differentiated medical diagnosis system. The network is easily trained by d...View more

Abstract:

A Self-Enforcing Network, which is a self-organized neural network, is introduced to develop a differentiated medical diagnosis system. The network is easily trained by data from medical websites and doctors; after training a user can insert the symptoms and obtains a possible diagnosis, or the names of drugs, which cause side effects according to the symptoms. The results show if the symptoms are sufficient to unambiguously identify a specific disease or if there are not enough symptoms to give a safe diagnosis. The described prototype includes concrete examples and shows the potential of such a network for diagnosis systems, in particular for worried unprofessional users.
Date of Conference: 24-29 July 2016
Date Added to IEEE Xplore: 03 November 2016
ISBN Information:
Electronic ISSN: 2161-4407
Publisher: IEEE
Conference Location: Vancouver, BC, Canada

References

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