Neural based diagnosis system
Algorithm, Desktop/Laptop, School Project, Java SE

Neural based diagnosis system


This research demonstrates an artificial neuro fuzzy networks can be applied to patient data for intelligent diagnostic support in healthcare. An IDSS in healthcare gathers and incorporates healthcare-specific domain knowledge and performs intelligent actions, including learning and reasoning while recommending clinical steps to take and justifying the outcomes. The utility of artificial neural network models lies in the fact that they can be used to infer a function from observations. This is particularly useful in applications where the complexity of the data or task makes the design of such a function by hand impractical.

This research project opens pathways into the study of the use of expert systems to help aid in the field of medicine. Managing knowledge in organizations to aid clinical decision-making requires information into actionable intelligence that can be interpreted by different functional workgroups within the organization. This research project will show how artificial intelligence can be used to analyze healthcare data and generate a representation of knowledge that can in turn be used for information and process modeling.



The aim of this project topic is the development of a neural based diagnostic support system for the diagnosis of the Ebola virus condition. The objective of this project is to achieve the following:

·        Designing a diagnostic tool system that will aid medical professionals in the diagnosis of Ebola virus infection.

·        Creation of an updatable Ebola virus diagnosis knowledge base where medical experts can supply info on diagnostic information they have gathered

·        Developing an application that with a user-friendly environment that is easily accessible for uploading information and also for the retrieval of information.


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