Machine learning and interpretation in neuroimaging
General Material Designation
[Book]
Other Title Information
international workshop, MLINI 2011, held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011 : revised selected and invited contributions /
First Statement of Responsibility
Georg Langs ... [et al.] (eds.)
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
New York :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
c2012
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource
SERIES
Series Title
Lecture notes in artificial intelligence
Series Title
LNCS sublibrary. SL 7, Artificial intelligence
Series Title
State-of-the-art survey
Volume Designation
7263.
ISSN of Series
0302-9743 ;
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index
SUMMARY OR ABSTRACT
Text of Note
Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning
PIECE
Title
OhioLINK electronic book center (Online)
Title
SpringerLink
PARALLEL TITLE PROPER
Parallel Title
MLINI 2011
Parallel Title
NIPS 2011
TOPICAL NAME USED AS SUBJECT
Artificial intelligence-- Medical applications, Congresses