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AIDS Treatments Efficiency Analysis Based-on DEA Models
Author: XuYin
Tutor: BianZuoPing
School: Tianjin University
Course: Operational Research and Cybernetics
Keywords: Data envelopment analysis (DEA) Decision-making unit (DMU) AIDS therapy Cost-effective β- chance constrained stochastic DEA effective
CLC: R512.91
Type: Master's thesis
Year: 2007
Downloads: 74
Quote: 0
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Abstract
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This paper uses data envelopment analysis (DEA) method to analyze the effectiveness of AIDS therapy in AIDS medical test tissue 193A . In dealing with a large number of AIDS therapy data using clustering method , has been the decision-making unit of the two groups have different meaning : a treatment phase , the decision-making units are grouped according to the patient's age and use therapy ; certain age segment patients , decision-making units are grouped by the use of therapy and treatment phase . And construct six DEA model analysis of these two groups of decision-making unit . On the stage of a treatment , grouped according to age and accept the therapy of AIDS patients to come to the decision-making unit . The use of three DEA model to evaluate the efficacy of four AIDS therapy in patients with different ages : the efficiency of the decision - making unit of the DEA model is given based on the output of the BCC ; The cost efficiency BCC model to evaluate the cost efficiency of each DMU ; based indirect output BCC model allows premise of substitution between the input and analysis of the efficiency of each decision - making unit . The optimization input to enable patients to select the most effective therapy combined with their age . Grouped according to accepted therapies and treatment phase , patients with an age to come to a decision-making unit . Additionally constructed the three DEA model four treatments in effectiveness of four treatment stages : β - chance constrained random BCC model output is taken into account in the analysis of the efficiency of the decision - making unit randomness ; DEA prediction model forecasts the efficacy of the move towards the next phase of various therapies ; indirect DEA prediction model allows input between alternative premise , to predict the efficacy of therapy the next phase toward . Patients of all ages should be treated with which therapy to at what stage , and the conclusion of the next phase of treatment which therapy should be used .
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CLC: > Medicine, health > Internal Medicine > Infectious disease > Viral infections > Acquired Immune Deficiency Syndrome ( AIDS AIDS)
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