On the Use of Decision Tree for Treatment Options in Medical  Decision

Mamman, Joseph Ndagatsa; Abdullahi, Muhammad Bashir; Alhassan, J. K.; Adepoju, Solomon A

Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/1803

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DC Field	Value	Language
dc.contributor.author	Mamman, Joseph Ndagatsa	-
dc.contributor.author	Abdullahi, Muhammad Bashir	-
dc.contributor.author	Alhassan, J. K.	-
dc.contributor.author	Adepoju, Solomon A	-
dc.date.accessioned	2021-06-06T22:13:21Z	-
dc.date.available	2021-06-06T22:13:21Z	-
dc.date.issued	2015	-
dc.identifier.citation	www.ijarcsse.com	en_US
dc.identifier.issn	2277 128X	-
dc.identifier.uri	http://repository.futminna.edu.ng:8080/jspui/handle/123456789/1803	-
dc.description.abstract	Decision making is becoming more complex and stressful for individuals and groups especially for medical professionals as a result of huge quantity of data. This paper is on the use of decision tree for treatment options in medical decision support systems. Decision tree was developed and an algorithm to identify optimal choice among complicated options in Surgery (Medical Operation) and Medical management (Drug Prescription) by calculating probabilities of events and incorporating patient evaluations of possible outcomes based on Average Life Year (ALY). This can help the medical professionals in taking decision among the available choices.	en_US
dc.publisher	International Journal of Advanced Research in Computer Science and Software Engineering	en_US
dc.relation.ispartofseries	Volume 5 Number 2;	-
dc.subject	Machine learning, Decision Tree, Decision making, Surgery, Medical Management, Average Life Year.	en_US
dc.title	On the Use of Decision Tree for Treatment Options in Medical Decision	en_US
dc.type	Article	en_US
Appears in Collections:	Computer Science

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