Studies in health technology and informatics
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Stud Health Technol Inform · Jan 2005
Tools for statistical analysis with missing data: application to a large medical database.
Missing data is a common feature of large data sets in general and medical data sets in particular. Depending on the goal of statistical analysis, various techniques can be used to tackle this problem. Imputation methods consist in substituting the missing values with plausible or predicted values so that the completed data can then be analysed with any chosen data mining procedure. ⋯ The control chart was established for the 3 imputation methods studied here, assuming a multivariate normal distribution of data. The use of this tool on a large medical database was then investigated. We show how the control chart can be used to assess the quality of the imputation process in the pre-processing step upstream of data mining procedures.
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This chapter describes a software process improvement framework, structured to ensure regulatory compliance for the software developed in medical devices. Software is becoming an increasingly important aspect of medical devices and medical device regulation. Medical devices can only be marketed if compliance and approval from the appropriate regulatory bodies of the Food and Drug Administration (US requirement), and the European Commission under its Medical Device Directives (CE marking requirement) is achieved.
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Cricothyroidotomy is an emergency procedure that is performed when the patient's airway is blocked, and less invasive attempts to clear it have failed. Cricothyroidotomy has been identified as an essential skill for military readiness. This training is relevant to more than 40,000 U. ⋯ Cadavers do not have the correct physiology. Mannequins do not adequately cover the full range of anatomical variations. In this paper, we describe our effort to build a computer-based cricothyroidotomy simulator to address these problems.
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Stud Health Technol Inform · Jan 2005
Integration of multiple ontologies in breast cancer pathology.
The diagnostic variability in pathology, widely reported in the literature, is partly due to the use of different classification systems by pathologists. The descriptions of morphological characteristics on the same image within different classification systems can be considered as different points of view of pathologists. Our aim is to represent the points of view of the experts in pathology during image interpretation and to propose a method ological and technical solution in order to implement interoperability between these points of view. ⋯ Our results show that the pathologists generally produce descriptions of the cases which do not follow rigorously the interpretation rules corresponding to the point of view they assert to adopt. While most of the concepts of local ontologies can be transcoded from a local ontology to another one (varying from 62.5 % to 100% according to the local ontology), the transcoding of a description which is valid according to a certain point of view, often results in a description which is not rigorously in accordance with the new point of view. These results underline the differences of interpretation rules existing in the different points of view.
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Stud Health Technol Inform · Jan 2004
Facilitating cancer research using natural language processing of pathology reports.
Many ongoing clinical research projects, such as projects involving studies associated with cancer, involve manual capture of information in surgical pathology reports so that the information can be used to determine the eligibility of recruited patients for the study and to provide other information, such as cancer prognosis. Natural language processing (NLP) systems offer an alternative to automated coding, but pathology reports have certain features that are difficult for NLP systems. This paper describes how a preprocessor was integrated with an existing NLP system (MedLEE) in order to reduce modification to the NLP system and to improve performance. ⋯ An evaluation of the system was performed using manually coded data from the research project's database as a gold standard. The evaluation outcome showed that the extended NLP system had a sensitivity of 90.6% and a precision of 91.6%. Results indicated that this system performed satisfactorily for capturing information for the cancer research project.