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245 1 0 _aMachine Learning and Interpretation in Neuroimaging
_h[electronic resource] :
_b4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, 2014, Revised Selected Papers /
_cedited by Irina Rish, Georg Langs, Leila Wehbe, Guillermo Cecchi, Kai-min Kevin Chang, Brian Murphy.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aX, 129 p. 30 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence ;
_v9444
_aLecture Notes in Computer Science
_v9444
505 0 _aNetworks and Decoding -- Multi-Task Learning for Interpretation of Brain Decoding Models -- The New Graph Kernels on Connectivity Networks for Identification of MCI -- Mapping Tractography Across Subjects -- Speech -- Automated speech analysis for psychosis evaluation -- Combining different modalities in classifying phonological categories -- Clinics and cognition -- Label-alignment-based Multi-task Feature Selection for Multimodal Classification of Brain Disease -- Leveraging Clinical Data to Enhance Localization of Brain Atrophy -- Estimating Learning Effects: A Short-Time Fourier Transform Regression Model for MEG Source Localization -- Causality and time-series -- Classification-based Causality Detection in Time Series -- Fast and Improved SLEX Analysis of High-dimensional Time Series -- Best paper awards: MLINI 2013 -- Predicting Short-Term Cognitive Change from Longitudinal Neuroimaging Analysis -- Hyperalignment of Multi-Subject fMRI Data by Synchronized Projections -- An oblique approach to prediction of conversion to Alzheimer's Disease with multikernel Gaussian Processes. .
520 _aThis book constitutes the revised selected papers from the 4th International Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2014, held in Montreal, QC, Canada, in December 2014 as a satellite event of the 11th annual conference on Neural Information Processing Systems, NIPS 2014. The 10 MLINI 2014 papers presented in this volume were carefully reviewed and selected from 17 submissions. They were organized in topical sections named: networks and decoding; speech; clinics and cognition; and causality and time-series. In addition, the book contains the 3 best papers presented at MLINI 2013.
650 0 _aPattern recognition.
650 0 _aOptical data processing.
650 0 _aArtificial intelligence.
650 0 _aApplication software.
650 0 _aMathematical statistics.
650 0 _aData mining.
650 1 4 _aPattern Recognition.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
650 2 4 _aImage Processing and Computer Vision.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I22021
650 2 4 _aArtificial Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I21000
650 2 4 _aInformation Systems Applications (incl. Internet).
_0https://scigraph.springernature.com/ontologies/product-market-codes/I18040
650 2 4 _aProbability and Statistics in Computer Science.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I17036
650 2 4 _aData Mining and Knowledge Discovery.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I18030
700 1 _aRish, Irina.
_eeditor.
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700 1 _aLangs, Georg.
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700 1 _aWehbe, Leila.
_eeditor.
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700 1 _aCecchi, Guillermo.
_eeditor.
_4edt
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700 1 _aChang, Kai-min Kevin.
_eeditor.
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700 1 _aMurphy, Brian.
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710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783319451756
830 0 _aLecture Notes in Artificial Intelligence ;
_v9444
830 0 _aLecture Notes in Computer Science ;
_v9444
856 4 0 _uhttps://doi.org/10.1007/978-3-319-45174-9
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