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LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00004316naa a2200433 4500
001oai:lup.lub.lu.se:949cbfbb-09f9-4b50-9086-161d3b305880
003SwePub
008160401s2012 | |||||||||||000 ||eng|
024a https://lup.lub.lu.se/record/29117092 URI
024a https://doi.org/10.1371/journal.pone.00343122 DOI
040 a (SwePub)lu
041 a engb eng
042 9 SwePub
072 7a art2 swepub-publicationtype
072 7a ref2 swepub-contenttype
100a Van Belle, Vanya M. C. A.4 aut
2451 0a A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology
264 c 2012-03-29
264 1b Public Library of Science (PLoS),c 2012
338 a electronic2 rdacarrier
520 a Background: Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients. Methods and Findings: We propose the interval coded scoring (ICS) system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems. Conclusions: The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges include extensions of the proposed methodology towards automated detection of interaction effects, multi-class decision support systems, prognosis and high-dimensional data.
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Reproduktionsmedicin och gynekologi0 (SwePub)302202 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Obstetrics, Gynaecology and Reproductive Medicine0 (SwePub)302202 hsv//eng
700a Van Calster, Ben4 aut
700a Timmerman, Dirk4 aut
700a Bourne, Tom4 aut
700a Bottomley, Cecilia4 aut
700a Valentin, Lilu Lund University,Lunds universitet,Obstetrisk, gynekologisk och prenatal ultraljudsdiagnostik,Forskargrupper vid Lunds universitet,Obstetric, Gynaecological and Prenatal Ultrasound Research,Lund University Research Groups4 aut0 (Swepub:lu)obst-lva
700a Neven, Patrick4 aut
700a Van Huffel, Sabine4 aut
700a Suykens, Johan A. K.4 aut
700a Boyd, Stephen4 aut
710a Obstetrisk, gynekologisk och prenatal ultraljudsdiagnostikb Forskargrupper vid Lunds universitet4 org
773t PLoS ONEd : Public Library of Science (PLoS)g 7:3q 7:3x 1932-6203
856u https://portal.research.lu.se/files/3810985/3350510.pdfx primaryx freey FULLTEXT
856u http://dx.doi.org/10.1371/journal.pone.0034312x freey FULLTEXT
856u https://doi.org/10.1371/journal.pone.0034312
8564 8u https://lup.lub.lu.se/record/2911709
8564 8u https://doi.org/10.1371/journal.pone.0034312

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