ProgramsView all programs
From the news
- Chancellor Amma Addresses the Parliament of World’s Religions
- Amrita Students Qualify for the European Mars Rover Challenge
Publication Type : Conference Proceedings
Publisher : Advances in Artificial Intelligence and Data Engineering, vol. 1133. Springer, pp. 393–409, 2021.
Source : Advances in Artificial Intelligence and Data Engineering, Springer, Volume 1133, p.393–409 (2021)
Keywords : Bayesian learning, Bayesian network, Expert systems
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2021
Abstract : A clinical decision support system (CDSS) is used as an aid in decision-making processes of health care providers in their day-to-day activities. This research attempts diagnosis of multiple diseases based on symptoms provided by patients. The work also recommends laboratory tests related to the predicted diseases and medications based on their results. The methodology adopted for implementation of CDSS is the Bayesian network approach. The modeling of the Bayesian network structure was undertaken in consultation with experts from medical domain. Clinical data has been used for estimation of network parameters such as conditional probability tables thereby bringing in machine learning into Bayesian methodology. The model developed is a learning model wherein the system input is saved for future training of the model. The results indicate that Bayesian approach is suitable for implementing a CDSS for multiple disease diagnosis. The proposed work will be useful towards increasing physicians throughput.
Cite this Research Publication : P. Laxmi, Gupta, D., Radhakrishnan, G., Amudha J., and Sharma, K., “Automatic Multi-disease Diagnosis and Prescription System Using Bayesian Network Approach for Clinical Decision Making”, Advances in Artificial Intelligence and Data Engineering, vol. 1133. Springer, pp. 393–409, 2021.