https://scholars.lib.ntu.edu.tw/handle/123456789/557480
標題: | A multiple measurements case-based reasoning method for predicting recurrent status of liver cancer patients | 作者: | Ping, Xiao-Ou Tseng, Yi-Ju Lin, Yan-Po Chiu, Hsiang-Ju FEI-PEI LAI JA-DER LIANG GUAN-TARN HUANG PEI-MING YANG |
公開日期: | 1-五月-2015 | 出版社: | Elsevier | 卷: | 69 | 起(迄)頁: | 12 | 來源出版物: | Computers in Industry | 摘要: | In general, the studies introducing the medical predictive models which frequently handle time series data by direct matching between pairs of features within sequences during calculation of similarity may have following limitations: (1) direct matching may not be a suitable matching because these paired cases by a fixed order may not be with the most similar temporal information, and (2) when two patients have different numbers of multiple cases, some cases may be ignored. For example, one patient with four cases and another one with five cases, only first four cases of these two patients are paired and the left one case may be ignored. In this paper, in order to dynamically determine matching pairs among cases and pair all cases between two patients, we propose a multiple measurements case-based reasoning (MMCBR) to be used for building liver cancer recurrence predictive models. MMCBR and single measurement case-based reasoning (SingleCBR) are evaluated and compared. According to experiment results in this study, the performance of MMCBR models is better than that of SingleCBR models. Multiple measurements accumulated during a period of time do have benefits for building predictive models with improved performance based on this proposed MMCBR method. ? 2015 Elsevier B.V. All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925937606&doi=10.1016%2fj.compind.2015.01.007&partnerID=40&md5=9321fcf1f1efbb54a6162d62a7d1e6a1 https://scholars.lib.ntu.edu.tw/handle/123456789/557480 |
ISSN: | 0166-3615 | DOI: | 10.1016/j.compind.2015.01.007 | SDG/關鍵字: | Diseases; Forecasting; Predictive analytics; Calculation of similarities; Liver cancers; Multiple measurements; Performance based; Predictive models; Recurrence; Temporal information; Time-series data; Case based reasoning |
顯示於: | 醫學系 |
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