NDLI: LEAD: a methodology for learning efficient approaches to medical diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Fakih, S.J. Das, T.K.
Copyright Year	1997
Abstract	Determining the most efficient use of diagnostic tests is one of the complex issues facing medical practitioners. With the soaring cost of healthcare, particularly in the US, there is a critical need for cutting costs of diagnostic tests, while achieving a higher level of diagnostic accuracy. This paper develops a learning based methodology that, based on patient information, recommends test(s) that optimize a suitable measure of diagnostic performance. A comprehensive performance measure is developed that accounts for the costs of testing, morbidity, and mortality associated with the tests, and time taken to reach diagnosis. The performance measure also accounts for the diagnostic ability of the tests. The methodology combines tools from the fields of data mining (rough set theory, in particular), utility theory, Markov decision processes (MDP), and reinforcement learning (RL). The rough set theory is used in extracting diagnostic information in the form of rules from the medical databases. Utility theory is used in bringing various nonhomogenous performance measures into one cost based measure. An MDP model together with an RL algorithm facilitates obtaining efficient testing strategies. The methodology is implemented on a sample problem of diagnosing solitary pulmonary nodule (SPN). The results obtained are compared with those from four alternative testing strategies. Our methodology holds significant promise to improve the process of medical diagnosis
Sponsorship	IEEE Engineering in Medicine and Biology Society IEEE Computer Society
Page Count	9
File Size	377897
Starting Page	220
Ending Page	228
File Format	PDF
ISSN	10897771
Volume Number	10
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Medical diagnosis Testing Costs Medical diagnostic imaging Data mining Set theory Utility theory Medical tests Medical services Optimization methods rough sets Markov decision processes (MDP) medical diagnosis reinforcement learning
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications Biotechnology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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