全部文献期刊学位论文会议报纸专利标准年鉴图书|学者科研项目
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作者:John Wallert , Mattia Tomasoni , Guy Madison ...
来源:[J].BMC Medical Informatics and Decision Making(IF 1.603), 2017, Vol.17 (1)Springer
摘要:Machine learning algorithms hold potential for improved prediction of all-cause mortality in cardiovascular patients, yet have not previously been developed with high-quality population data. This study compared four popular machine learning algorithms trained on unselected, nati...
作者:Sherif Sakr , Radwa Elshawi , Amjad M. Ahmed ...
来源:[J].BMC Medical Informatics and Decision Making(IF 1.603), 2017, Vol.17 (1)Springer
摘要:... Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined categories. The aim of this study is to present an evaluation and comparison of how machine learning techniques can be applied on medical r...
作者:Glenn N. Saxe , Sisi Ma , Jiwen Ren ...
来源:[J].BMC Psychiatry(IF 2.233), 2017, Vol.17 (1)Springer
摘要:... Machine Learning (ML) computational methods have yielded strong results in recent applications across many diseases and data types, yet they have not been previously applied to childhood PTSD. Since these methods have not been applied to this complex and debilitating dis...
作者:Brian Connolly , K. Bretonnel Cohen , Daniel Santel ...
来源:[J].BMC Bioinformatics(IF 3.024), 2017, Vol.18 (1)Springer
摘要:... Yet, machine learning, which supports this care process has been limited to categorical results. To maximize its usefulness, it is important to find novel approaches that calibrate the ML output with a likelihood scale. Current state-of-the-art calibration methods are general...
作者:Gregory P. Way , Robert J. Allaway , Stephanie J. Bouley ...
来源:[J].BMC Genomics(IF 4.397), 2017, Vol.18 (1)Springer
摘要:... NF1 inactivation may alter the transcriptional landscape of a tumor and allow a machine learning classifier to detect which tumors will benefit from synthetic lethal molecules.
作者:Richard Newton , Lorenz Wernisch
来源:[J].BMC Genomics(IF 4.397), 2017, Vol.18 (1)Springer
摘要:... In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model.
作者:Jose Cleydson F. Silva , Thales F. M. Carvalho , Marcos F. Basso ...
来源:[J].BMC Bioinformatics(IF 3.024), 2017, Vol.18 (1)Springer
摘要:... Data mining approaches, mainly supported by machine learning (ML) techniques, are a natural means for high-throughput data analysis in the context of genomics, transcriptomics, proteomics, and metabolomics.
作者:Colin Bellinger , Mohomed Shazan Mohomed Jabbar , Osmar Zaïane ...
来源:[J].BMC Public Health(IF 2.076), 2017, Vol.17 (1)Springer
摘要:... To this end, data mining and machine learning algorithms are increasingly being applied to air pollution epidemiology.
作者:Santosh Philips , Heng-Yi Wu , Lang Li
来源:[J].BMC Bioinformatics(IF 3.024), 2017, Vol.18 (11)Springer
摘要:... Here we propose a machine learning method to mining through publicly available literature on RNA interference with the goal of identifying genes essential for cell survival.
作者:Carl Tony Fakhry , Prajna Kulkarni , Ping Chen ...
来源:[J].BMC Genomics(IF 4.397), 2017, Vol.18 (1)Springer
摘要:... In such cases, machine-learning approaches can be used to predict novel sRNAs in a given class.

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