28 research outputs found
Automatic construction of rule-based ICD-9-CM coding systems
Background: In this paper we focus on the problem of automatically constructing ICD-9-CM coding systems for radiology reports. ICD-9-CM codes are used for billing purposes by health institutes and are assigned to clinical records manually following clinical treatment. Since this labeling task requires expert knowledge in the field of medicine, the process itself is costly and is prone to errors as human annotators have to consider thousands of possible codes when assigning the right ICD-9-CM labels to a document. In this study we use the datasets made available for training and testing automated ICD-9-CM coding systems by the organisers of an International Challenge on Classifying Clinical Free Text Using Natural Language Processing in spring 2007. The challenge itself was dominated by entirely or partly rule-based systems that solve the coding task using a set of hand crafted expert rules. Since the feasibility of the construction of such systems for thousands of ICD codes is indeed questionable, we decided to examine the problem of automatically constructing similar rule sets that turned out to achieve a remarkable accuracy in the shared task challenge. Results: Our results are very promising in the sense that we managed to achieve comparable results with purely hand-crafted ICD-9-CM classifiers. Our best model got a 90.26 % F measure on the training dataset and an 88.93 % F measure on the challenge test dataset, using the micro-averaged Fβ=1 measure, the official evaluatio
Automatic medical encoding with SNOMED categories
BACKGROUND: In this paper, we describe the design and preliminary evaluation of a new type of tools to speed up the encoding of episodes of care using the SNOMED CT terminology. METHODS: The proposed system can be used either as a search tool to browse the terminology or as a categorization tool to support automatic annotation of textual contents with SNOMED concepts. The general strategy is similar for both tools and is based on the fusion of two complementary retrieval strategies with thesaural resources. The first classification module uses a traditional vector-space retrieval engine which has been fine-tuned for the task, while the second classifier is based on regular variations of the term list. For evaluating the system, we use a sample of MEDLINE. SNOMED CT categories have been restricted to Medical Subject Headings (MeSH) using the SNOMED-MeSH mapping provided by the UMLS (version 2006). RESULTS: Consistent with previous investigations applied on biomedical terminologies, our results show that performances of the hybrid system are significantly improved as compared to each single module. For top returned concepts, a precision at high ranks (P0) of more than 80% is observed. In addition, a manual and qualitative evaluation on a dozen of MEDLINE abstracts suggests that SNOMED CT could represent an improvement compared to existing medical terminologies such as MeSH. CONCLUSION: Although the precision of the SNOMED categorizer seems sufficient to help professional encoders, it is concluded that clinical benchmarks as well as usability studies are needed to assess the impact of our SNOMED encoding method in real settings. AVAILABILITIES : The system is available for research purposes on: http://eagl.unige.ch/SNOCat
Models of Decisionmaking: Their Uses and Limitations
This paper critically surveys explicit models of actual decisionmaking. How are the models derived? How are the models used and evaluated? What conceivable value can the models have? Are there better practices for creating and using models of decisionmaking? Contact
Process Models and Program Evaluation: the Impact of General Revenue Sharing on Municipal Fiscal Behavior.
Ph.D.Public administrationUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/157448/1/7609440.pd
Reply to Professor Harsanyi
Reply to Harsanyi, J. C. 1982. Comment---Subjective probability and the theory of games: comments on Kadane and Larkey's paper. Management Sci. 28 (2) 120--124.
The Confusion of Is and Ought in Game Theoretic Contexts
This paper explores the distinction between normative and positive theoretical statements in a game theoretic context from a Bayesian perspective. Normative and positive theoretical statements are often confused in decision making research. The confusion results from some unique epistemological and methodological problems associated with cognitive behavior as an object for scientific inquiry. The confusion persists because of poor model validation procedures which are themselves further complicated by the confusion. The confusion greatly impedes the development of more useful prescriptions for and predictions of human decision behavior. From a Bayesian perspective which acknowledges the importance of incomplete information and imperfect theories of behavior, the confusion is unnecessary.game theory
The Confusion of Is and Ought in Game Theoretic Contexts
This paper explores the distinction between normative and positive theoretical statements in
a game theoretic context from a Bayesian perspective. Normative and positive theoretical
statements are often confused in decision making research. The confusion results from some
unique epistemological and methodological problems associated with cognitive behavior as an
object for scientific inquiry. The confusion persists because of poor model validation procedures
which are themselves further complicated by the confusion. The confusion greatly
impedes the development of more useful prescriptions for and predictions of human decision
behavior. From a Bayesian perspective which acknowledges the importance of incomplete
information and imperfect theories of behavior, the confusion is unnecessary
Reply to Professor Harsanyi
Response to HARSANYI, J. C., "Subjective Probability and the Theory of Games: Comments on Kadane and Larkey's
Paper," Management Science Vol. 28, No. 2 (Feb., 1982