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- W1596593583 abstract "A key purpose of building a model from clinical data is to predict the outcomes of future individual patients. This work introduces a Bayesian patient-specific predictive framework for constructing predictive models from data that are optimized to predict well for a particular patient case. The construction of such patient-specific models is influenced by the particular history, symptoms, laboratory results, and other features of the patient case at hand. This approach is in contrast to the commonly used population-wide models that are constructed to perform well on average on all future cases.The new patient-specific method described in this research uses Bayesian network models, carries out Bayesian model averaging over a set of models to predict the outcome of interest for the patient case at hand, and employs a patient-specific heuristic to locate a set of suitable models to average over. Two versions of the method are developed that differ in the representation used for the conditional probability distributions in the Bayesian networks. One version uses a representation that captures only the so called global structure among the variables of a Bayesian network and the second representation captures additional local structure among the variables. The patient-specific methods were experimentally evaluated on one synthetic dataset, 21 UCI datasets and three medical datasets. Their performance was measured using five different performance measures and compared to that of several commonly used methods for constructing predictive models including naive Bayes, C4.5 decision tree, logistic regression, neural networks, k-Nearest Neighbor and Lazy Bayesian Rules. Over all the datasets, both patient-specific methods performed better on average on all performance measures and against all the comparison algorithms. The global structure method that performs Bayesian model averaging in conjunction with the patient-specific search heuristic had better performance than either model selection with the patient-specific heuristic or non-patient-specific Bayesian model averaging. However, the additional learning of local structure by the local structure method did not lead to significant improvements over the use of global structure alone. The specific implementation limitations of the local structure method may have limited its performance." @default.
- W1596593583 created "2016-06-24" @default.
- W1596593583 creator A5036362467 @default.
- W1596593583 date "2007-01-01" @default.
- W1596593583 modified "2023-09-27" @default.
- W1596593583 title "LEARNING PATIENT-SPECIFIC MODELS FROM CLINICAL DATA" @default.
- W1596593583 cites W1481566577 @default.
- W1596593583 cites W1492518391 @default.
- W1596593583 cites W1509515766 @default.
- W1596593583 cites W1520493155 @default.
- W1596593583 cites W1523842520 @default.
- W1596593583 cites W1528489993 @default.
- W1596593583 cites W1530964327 @default.
- W1596593583 cites W1534519688 @default.
- W1596593583 cites W1544444076 @default.
- W1596593583 cites W1549872659 @default.
- W1596593583 cites W1550825417 @default.
- W1596593583 cites W1551066950 @default.
- W1596593583 cites W1551136530 @default.
- W1596593583 cites W1559060276 @default.
- W1596593583 cites W1563088657 @default.
- W1596593583 cites W1570448133 @default.
- W1596593583 cites W1572250146 @default.
- W1596593583 cites W1579410832 @default.
- W1596593583 cites W1585743408 @default.
- W1596593583 cites W1597018937 @default.
- W1596593583 cites W1599263113 @default.
- W1596593583 cites W1603903339 @default.
- W1596593583 cites W1610836425 @default.
- W1596593583 cites W1689445748 @default.
- W1596593583 cites W1698663318 @default.
- W1596593583 cites W1817561967 @default.
- W1596593583 cites W1827261456 @default.
- W1596593583 cites W1835849596 @default.
- W1596593583 cites W1864566053 @default.
- W1596593583 cites W1868985710 @default.
- W1596593583 cites W1875283242 @default.
- W1596593583 cites W1912982817 @default.
- W1596593583 cites W1934306740 @default.
- W1596593583 cites W1965894730 @default.
- W1596593583 cites W1968181674 @default.
- W1596593583 cites W1972182967 @default.
- W1596593583 cites W1977135436 @default.
- W1596593583 cites W1978544678 @default.
- W1596593583 cites W1981054279 @default.
- W1596593583 cites W1981976602 @default.
- W1596593583 cites W1988386616 @default.
- W1596593583 cites W1989926363 @default.
- W1596593583 cites W1999327911 @default.
- W1596593583 cites W2008906462 @default.
- W1596593583 cites W2010640878 @default.
- W1596593583 cites W2013567125 @default.
- W1596593583 cites W2017337590 @default.
- W1596593583 cites W2029948740 @default.
- W1596593583 cites W2044055744 @default.
- W1596593583 cites W2048537487 @default.
- W1596593583 cites W2051483504 @default.
- W1596593583 cites W2052466231 @default.
- W1596593583 cites W2069429507 @default.
- W1596593583 cites W2073241381 @default.
- W1596593583 cites W2076056672 @default.
- W1596593583 cites W2084812512 @default.
- W1596593583 cites W2096123080 @default.
- W1596593583 cites W2099111195 @default.
- W1596593583 cites W2104670598 @default.
- W1596593583 cites W2111051773 @default.
- W1596593583 cites W2115091609 @default.
- W1596593583 cites W2122111042 @default.
- W1596593583 cites W2123774149 @default.
- W1596593583 cites W2129531883 @default.
- W1596593583 cites W2137587467 @default.
- W1596593583 cites W2145818505 @default.
- W1596593583 cites W2150020424 @default.
- W1596593583 cites W2155236584 @default.
- W1596593583 cites W2157298598 @default.
- W1596593583 cites W2157825442 @default.
- W1596593583 cites W2158418996 @default.
- W1596593583 cites W2163166770 @default.
- W1596593583 cites W2163757302 @default.
- W1596593583 cites W2169152096 @default.
- W1596593583 cites W2170112109 @default.
- W1596593583 cites W2320270386 @default.
- W1596593583 cites W2339500526 @default.
- W1596593583 cites W2341811425 @default.
- W1596593583 cites W2397866408 @default.
- W1596593583 cites W2407180081 @default.
- W1596593583 cites W2962899638 @default.
- W1596593583 cites W2963139738 @default.
- W1596593583 cites W3136726919 @default.
- W1596593583 cites W32516901 @default.
- W1596593583 cites W76332699 @default.
- W1596593583 cites W97420631 @default.
- W1596593583 cites W2107978811 @default.
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