Abstract
Despite all the standardization efforts made, medical diagnosis is still regarded as an art owing to the fact that that medical diagnosis requires an expertise in handling the uncertainty which is unavailable in today's computing machinery. Though artificial intelligence is not a new concept it has been widely recognized as a new technology in computer science. Numerous areas such as education, business, medical and manufacturing have made use of artificial intelligence. Problem statement: The proposed study investigated the potential of artificial intelligence techniques principally for medical applications. Neural network algorithms could possible provide an enhanced solution for medical problems. This study analyzed the application of artificial intelligence in conventional hepatitis B diagnosis. Approach: In this research, an intelligent system that worked on basis of logical inference utilized to make a decision on the type of hepatitis that is likely to appear for a patient, if it is hepatitis B or not. Then kohonen's self-organizing map network was applied to hepatitis data for predictions regarding the Hepatitis B which gives severity level on the patient. Results: SOM which is a class of unsupervised network was used as a classifier to predict the accuracy of Hepatitis B. Conclusion: We concluded that the proposed model gives faster and more accurate prediction of hepatitis B and it works as promising tool for predicting of routine hepatitis B from the clinical laboratory data.
Highlights
The utilization of Artificial Intelligence (AI) in medical applications has extensively been recognized in the recent past
Our study aims at identifying the genomic markers of the Hepatitis B Virus (HBV) and clinical information which are utilized to predict occurrence of liver cancer and response to therapy
Our study aims to diagnosis Hepatitis B virus disease and predict the severity level by imbedding an intelligent system with a classification model for HBV Deoxyribo-Nucleic Acid (DNA) and clinical data
Summary
The utilization of Artificial Intelligence (AI) in medical applications has extensively been recognized in the recent past. Our study aims to diagnosis Hepatitis B virus disease and predict the severity level by imbedding an intelligent system with a classification model for HBV DNA and clinical data. The proposed study utilizes Neural Network for the diagnosis of Hepatitis B virus. Intelligent system for hepatitis B diagnosis: The proposed research intends to Apply Artificial Neural Networks (ANNs) and related analysis methods to Health care, precisely to the management of Hepatitis B virus patient. The research is carried out to convert the diagnosis process into an over flow diagram or the effective parameter datasets (machine readable format) for the Hepatitis B disease followed by the evaluation the effective set of symptoms by utilizing expert systems on basis of Logical inference and artificial neural network techniques. Since the identical inputs are anticipated to stay adjacent to each other, the aforesaid organization is assumed to form a SOM map
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
