Markov Logic Based Inference Engine for CDSS
CDSS (Clinical Decision Support System) is typically a diagnostic application and a modern technology that can be employed to provide standardized and quality medical facilities to the medical patients especially when expert doctors are not available at the medical centres. These days the use of t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Mehran University of Engineering and Technology
2017-01-01
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| Series: | Mehran University Research Journal of Engineering and Technology |
| Subjects: | |
| Online Access: | http://publications.muet.edu.pk/research_papers/pdf/pdf1449.pdf |
| Summary: | CDSS (Clinical Decision Support System) is typically a diagnostic application and a modern technology
that can be employed to provide standardized and quality medical facilities to the medical patients
especially when expert doctors are not available at the medical centres. These days the use of the CDSSs
is quite common in medical practice at remote areas. A CDSS can be very helpful not only in preventive
health care but also in computerized diagnosis. However, a typical problem of CDSS based diagnosis is
uncertainty. Typically, an ambiguity can occur when a patient is not able to explain the symptoms of his
disease in a better way. The typically used forward chaining mechanisms in rule based decision support
systems perform reasoning with uncertain data. ML (Markov Logic) is a new technique that has ability
to deal with uncertainty of data by integrating FOL (First-Order-Logic) with probabilistic graphical
models. In this paper, we have proposed the architecture of a ML based inference engine for a rule based
CDSS and we have also presented an algorithm to use ML based forward chaining mechanism in the proposed inference engine. The results of the experiments show that the proposed inference engine would be intelligent enough to diagnose a patient?s disease even from uncertain or incomplete/partial
information. |
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| ISSN: | 0254-7821 2413-7219 |