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標(biāo)題: Titlebook: Efficacy Analysis in Clinical Trials an Update; Efficacy Analysis in Ton J. Cleophas,Aeilko H. Zwinderman Textbook 2019 Springer Nature Swi [打印本頁(yè)]

作者: 富裕    時(shí)間: 2025-3-21 18:43
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書目名稱Efficacy Analysis in Clinical Trials an Update讀者反饋學(xué)科排名





作者: 供過于求    時(shí)間: 2025-3-21 20:22

作者: Aprope    時(shí)間: 2025-3-22 00:37
Optimal-Scaling for Efficacy Analysis,ms on drug efficacy scores was tested, both traditionally and with the help of machine learning..Traditional efficacy analysis consisted of.Machine learning efficacy analysis consisted of optimal-scaling methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: 卵石    時(shí)間: 2025-3-22 08:37

作者: Blood-Vessels    時(shí)間: 2025-3-22 09:19

作者: Decimate    時(shí)間: 2025-3-22 13:21
Evolutionary-Operations for Efficacy Analysis,d with the help of machine learning..Traditional efficacy analysis was composed of.Poisson statistics,.z-tests..Machine learning efficacy analysis was composed of evolutionary-operation methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: Decimate    時(shí)間: 2025-3-22 17:56

作者: nascent    時(shí)間: 2025-3-23 00:21

作者: goodwill    時(shí)間: 2025-3-23 02:01

作者: 取回    時(shí)間: 2025-3-23 07:12

作者: 執(zhí)    時(shí)間: 2025-3-23 10:12
Ensembled-Correlations for Efficacy Analysis,he help of machine learning..Traditional efficacy analysis consisted of.simple linear regressions,.multiple linear regressions,.Bonferroni’s adjustments..Machine learning efficacy analysis consisted of ensembled-correlation methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: 凹槽    時(shí)間: 2025-3-23 17:40
Gamma-Distributions for Efficacy Analysis,lp of machine learning..Traditional efficacy analysis consisted of.simple linear regressions,.multiple linear regressions,.Bonferroni’s adjustments..Machine learning efficacy analysis consisted of gamma-distribution methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: instill    時(shí)間: 2025-3-23 21:57
https://doi.org/10.1007/978-1-4899-6134-1ses of variance, both paired and unpaired, are explained as methods for testing the significance of difference between a new and control treatment. Instead of treatment modalities as causal outcome factors, many more causal factors of health and sickness can be tested in clinical trials, like psycho
作者: 新奇    時(shí)間: 2025-3-23 22:59
Demanding Energy: An Introduction,ms on drug efficacy scores was tested, both traditionally and with the help of machine learning..Traditional efficacy analysis consisted of.Machine learning efficacy analysis consisted of optimal-scaling methods..The machine learning methods provided better sensitivity of testing, and were more info
作者: 冥界三河    時(shí)間: 2025-3-24 06:17
A Shared (Cost) Burden (Pillar Three), and with the help of machine learning..Traditional efficacy analysis was consisted of.Machine learning efficacy analysis consisted of ratio-statistic methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: 大喘氣    時(shí)間: 2025-3-24 08:16
https://doi.org/10.1007/978-3-540-78809-6achine learning..Traditional efficacy analysis consisted of.Machine learning efficacy analysis consisted of complex-samples methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: 愛哭    時(shí)間: 2025-3-24 13:34

作者: delta-waves    時(shí)間: 2025-3-24 17:02
https://doi.org/10.1007/978-1-4615-6805-6d with the help of machine learning..Traditional efficacy analysis was composed of.Poisson statistics,.z-tests..Machine learning efficacy analysis was composed of evolutionary-operation methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: AGONY    時(shí)間: 2025-3-24 20:26

作者: 噱頭    時(shí)間: 2025-3-25 01:20
Daria Smirnova,Tatiana Smirnova,Paul Cummingnalysis was composed of.discretization of continuous predictors,.three dimensional bars of effects versus outcome,.crosstabs with chi-square statistics..Machine learning efficacy analysis was composed of high-risk-bin methods..The machine learning methods provided better sensitivity of testing, and
作者: 言行自由    時(shí)間: 2025-3-25 05:48

作者: DUST    時(shí)間: 2025-3-25 11:30
DCM als intervenierende Operation, and with the help of machine learning..Traditional efficacy analysis consisted of.discretization of continuous predictors,.simple linear regressions..Machine learning efficacy analysis consisted of cluster-analysis methods..The machine learning methods provided better sensitivity of testing, and we
作者: 業(yè)余愛好者    時(shí)間: 2025-3-25 12:22

作者: 取之不竭    時(shí)間: 2025-3-25 18:30
https://doi.org/10.1007/978-3-031-55440-7ted, both traditionally, and with the help of machine learning..Traditional efficacy analysis consisted of.discretization of continuous predictors,.crosstabs with chi-square statistics..Machine learning efficacy analysis consisted of binary decision-tree methods..The machine learning methods provide
作者: 不朽中國(guó)    時(shí)間: 2025-3-25 23:23

作者: 違抗    時(shí)間: 2025-3-26 00:43
Dementia and the Advance Directiveof death were tested, both traditionally, and with the help of machine learning..Traditional efficacy analysis consisted of.one-way analyses of variance,.3?×?2 crosstabs with 3?×?2 chi-square statistics,.3 dimensional bars of treatment modalities versus outcomes..Machine learning efficacy analysis c
作者: Harass    時(shí)間: 2025-3-26 05:32

作者: 有偏見    時(shí)間: 2025-3-26 08:52
History and Neurological Examination,ms on drug efficacy scores was tested, both traditionally and with the help of machine learning..Traditional efficacy analysis consisted of.discretization of continuous predictors,.3?×?2 crosstabs with 3?×?2 chi-square statistics..Machine learning efficacy analysis was composed of neural-network met
作者: 遺留之物    時(shí)間: 2025-3-26 12:49
https://doi.org/10.1007/978-3-319-75259-4ne learning..Traditional efficacy analysis consisted of.Machine learning efficacy analysis consisted of ensembled-accuracy methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: 一條卷發(fā)    時(shí)間: 2025-3-26 18:29

作者: SOW    時(shí)間: 2025-3-27 00:35
Alpha-Synuclein in Cerebrospinal Fluidlp of machine learning..Traditional efficacy analysis consisted of.simple linear regressions,.multiple linear regressions,.Bonferroni’s adjustments..Machine learning efficacy analysis consisted of gamma-distribution methods..The machine learning methods provided better sensitivity of testing, and we
作者: Increment    時(shí)間: 2025-3-27 03:27

作者: Painstaking    時(shí)間: 2025-3-27 06:47

作者: MELON    時(shí)間: 2025-3-27 12:32

作者: 相容    時(shí)間: 2025-3-27 14:01
A Shared (Cost) Burden (Pillar Three), and with the help of machine learning..Traditional efficacy analysis was consisted of.Machine learning efficacy analysis consisted of ratio-statistic methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: Bravura    時(shí)間: 2025-3-27 20:34
https://doi.org/10.1007/978-3-540-78809-6achine learning..Traditional efficacy analysis consisted of.Machine learning efficacy analysis consisted of complex-samples methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: Amnesty    時(shí)間: 2025-3-28 00:21
https://doi.org/10.1007/978-1-4615-6805-6d with the help of machine learning..Traditional efficacy analysis was composed of.Poisson statistics,.z-tests..Machine learning efficacy analysis was composed of evolutionary-operation methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: Dislocation    時(shí)間: 2025-3-28 04:30
Daria Smirnova,Tatiana Smirnova,Paul Cummingnalysis was composed of.discretization of continuous predictors,.three dimensional bars of effects versus outcome,.crosstabs with chi-square statistics..Machine learning efficacy analysis was composed of high-risk-bin methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: relieve    時(shí)間: 2025-3-28 10:01

作者: 敬禮    時(shí)間: 2025-3-28 12:03

作者: 1分開    時(shí)間: 2025-3-28 16:13

作者: Coronary-Spasm    時(shí)間: 2025-3-28 21:55
Martin N. Dichter MScN, RN,Gabriele Meyerhe help of machine learning..Traditional efficacy analysis consisted of.simple linear regressions,.multiple linear regressions,.Bonferroni’s adjustments..Machine learning efficacy analysis consisted of ensembled-correlation methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: FLAG    時(shí)間: 2025-3-28 23:24

作者: 傷心    時(shí)間: 2025-3-29 03:34

作者: 是限制    時(shí)間: 2025-3-29 07:15
Traditional and Machine-Learning Methods for Efficacy Analysis,ete and discretized predictors three dimensional bar charts and chi-square tests are appropriate. We live in an era of machine learning, and, also in this edition, traditional methods for efficacy analysis will be tested against machine learning methodologies. A summary of methodologies is given in this chapter.
作者: 共同給與    時(shí)間: 2025-3-29 12:03
Textbook 2019 all of the machine learning analyses were tested against traditional analyses. Step by step statistics for self-assessments are included..The authors conclude, that machine learning is often more informative, and provides better sensitivities of testing than traditional analytic methods do.
作者: Root494    時(shí)間: 2025-3-29 16:51
onfirms, that machine learning methodologies provide better .Machine learning and big data is hot. It is, however, virtually unused in clinical trials. This is so, because randomization is applied to even out multiple variables..Modern medical computer files often involve hundreds of variables like
作者: 藕床生厭倦    時(shí)間: 2025-3-29 22:37

作者: BOON    時(shí)間: 2025-3-30 00:18
The clinical features of the dementias,ression model of exponential function..Machine learning efficacy analysis consisted of automatic-Newton modeling..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: innate    時(shí)間: 2025-3-30 07:48
Yael R. Zweig MSN, ANP-BC, GNP-BC regressions..Machine learning efficacy analysis was composed of balanced-iterative-reducing-hierarchy methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: 大溝    時(shí)間: 2025-3-30 09:04

作者: 含糊其辭    時(shí)間: 2025-3-30 14:55

作者: 挖掘    時(shí)間: 2025-3-30 17:45

作者: delusion    時(shí)間: 2025-3-30 23:29

作者: Heresy    時(shí)間: 2025-3-31 02:29

作者: 擦試不掉    時(shí)間: 2025-3-31 08:16
Automatic-Newton-Modeling for Efficacy Analysis,ression model of exponential function..Machine learning efficacy analysis consisted of automatic-Newton modeling..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: 蚊帳    時(shí)間: 2025-3-31 09:44

作者: Notify    時(shí)間: 2025-3-31 16:24

作者: debunk    時(shí)間: 2025-3-31 21:05
Automatic-Data-Mining for Efficacy Analysis,ce,.3?×?2 crosstabs with 3?×?2 chi-square statistics,.3 dimensional bars of treatment modalities versus outcomes..Machine learning efficacy analysis consisted of automatic-data-mining methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: constellation    時(shí)間: 2025-3-31 22:52
Neural-Networks for Efficacy Analysis,tion of continuous predictors,.3?×?2 crosstabs with 3?×?2 chi-square statistics..Machine learning efficacy analysis was composed of neural-network methods..The machine learning methods provided better sensitivity of testing, and were more informative.
作者: 吝嗇性    時(shí)間: 2025-4-1 04:15

作者: 向外供接觸    時(shí)間: 2025-4-1 06:53
Traditional and Machine-Learning Methods for Efficacy Analysis,ses of variance, both paired and unpaired, are explained as methods for testing the significance of difference between a new and control treatment. Instead of treatment modalities as causal outcome factors, many more causal factors of health and sickness can be tested in clinical trials, like psycho
作者: configuration    時(shí)間: 2025-4-1 12:29

作者: chiropractor    時(shí)間: 2025-4-1 18:22

作者: 帶來墨水    時(shí)間: 2025-4-1 20:57
Complex-Samples for Efficacy Analysis,achine learning..Traditional efficacy analysis consisted of.Machine learning efficacy analysis consisted of complex-samples methods..The machine learning methods provided better sensitivity of testing, and were more informative.




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