Related references
Note: Only part of the references are listed.Deep learning-based clustering approaches for bioinformatics
Md Rezaul Karim et al.
BRIEFINGS IN BIOINFORMATICS (2021)
Understanding the impact of preprocessing pipelines on neuroimaging cortical surface analyses
Nikhil Bhagwat et al.
GIGASCIENCE (2021)
Using Machine Learning and Structural Neuroimaging to Detect First Episode Psychosis: Reconsidering the Evidence
Sandra Vieira et al.
SCHIZOPHRENIA BULLETIN (2020)
Universality of deep convolutional neural networks
Ding-Xuan Zhou
APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS (2020)
Detecting schizophrenia at the level of the individual: relative diagnostic value of whole-brain images, connectome-wide functional connectivity and graph-based metrics
Du Lei et al.
PSYCHOLOGICAL MEDICINE (2020)
Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis
Luigi A. Maglanoc et al.
HUMAN BRAIN MAPPING (2020)
Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics
Tong He et al.
NEUROIMAGE (2020)
Application of deep canonically correlated sparse autoencoder for the classification of schizophrenia
Gang Li et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)
Alcoholism identification via convolutional neural network based on parametric ReLU, dropout, and batch normalization
Shui-Hua Wang et al.
NEURAL COMPUTING & APPLICATIONS (2020)
A multimodal neuroimaging classifier for alcohol dependence
Matthias Guggenmos et al.
SCIENTIFIC REPORTS (2020)
Identifying Schizophrenia Using Structural MRI With a Deep Learning Algorithm
Jihoon Oh et al.
FRONTIERS IN PSYCHIATRY (2020)
DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI
Atif Riaz et al.
JOURNAL OF NEUROSCIENCE METHODS (2020)
ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
Paul M. Thompson et al.
TRANSLATIONAL PSYCHIATRY (2020)
Optimising network modelling methods for fMRI
Usama Pervaiz et al.
NEUROIMAGE (2020)
MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide
Vishnu M. Bashyam et al.
BRAIN (2020)
Inferring disease subtypes from clusters in explanation space
Marc-Andre Schulz et al.
SCIENTIFIC REPORTS (2020)
Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets
Marc-Andre Schulz et al.
NATURE COMMUNICATIONS (2020)
A Multichannel Deep Neural Network Model Analyzing Multiscale Functional Brain Connectome Data for Attention Deficit Hyperactivity Disorder Detection
Ming Chen et al.
RADIOLOGY-ARTIFICIAL INTELLIGENCE (2020)
The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features
Philip A. Spechler et al.
EUROPEAN JOURNAL OF NEUROSCIENCE (2019)
Neurobiology of the major psychoses: a translational perspective on brain structure and function-the FOR2107 consortium
Tilo Kircher et al.
EUROPEAN ARCHIVES OF PSYCHIATRY AND CLINICAL NEUROSCIENCE (2019)
How to control for confounds in decoding analyses of neuroimaging data
Lukas Snoek et al.
NEUROIMAGE (2019)
Diagnostic neuroimaging markers of obsessive-compulsive disorder: Initial evidence from structural and functional MRI studies
Willem Bruin et al.
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY (2019)
Segmentation and clustering in brain MRI imaging
Golrokh Mirzaei et al.
REVIEWS IN THE NEUROSCIENCES (2019)
The Missing Diversity in Human Genetic Studies
Giorgio Sirugo et al.
CELL (2019)
Artificial Intelligence and Black-Box Medical Decisions: Accuracy versus Explainability
Alex John London
HASTINGS CENTER REPORT (2019)
Deep neural networks in psychiatry
Daniel Durstewitz et al.
MOLECULAR PSYCHIATRY (2019)
Unmasking Clever Hans predictors and assessing what machines really learn
Sebastian Lapuschkin et al.
NATURE COMMUNICATIONS (2019)
Evaluating the evidence for biotypes of depression: Methodological replication and extension of Drysdale et al. (2017)
Richard Dinga et al.
NEUROIMAGE-CLINICAL (2019)
An Introduction to Machine Learning for Clinicians
Michael Rowe
ACADEMIC MEDICINE (2019)
A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures
Yong Yu et al.
NEURAL COMPUTATION (2019)
The value of hippocampal volume, shape, and texture for 11-year prediction of dementia: a population-based study
Hakim C. Achterberg et al.
NEUROBIOLOGY OF AGING (2019)
Machine Learning in Medicine
Alvin Rajkomar et al.
NEW ENGLAND JOURNAL OF MEDICINE (2019)
Alcoholism Identification Based on an AlexNet Transfer Learning Model
Shui-Hua Wang et al.
FRONTIERS IN PSYCHIATRY (2019)
3D-CNN based discrimination of schizophrenia using resting-state fMRI
Muhammad Naveed Iqbal Qureshi et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2019)
Machine learning in resting-state fMRI analysis
Meenakshi Khosla et al.
MAGNETIC RESONANCE IMAGING (2019)
Conceptualizing mental disorders as deviations from normative functioning
Andre F. Marquand et al.
MOLECULAR PSYCHIATRY (2019)
Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer
Jakob Nikolas Kather et al.
NATURE MEDICINE (2019)
Transfer Learning Assisted Classification and Detection of Alzheimer's Disease Stages Using 3D MRI Scans
Muazzam Maqsood et al.
SENSORS (2019)
Layer-Wise Relevance Propagation for Explaining Deep Neural Network Decisions in MRI-Based Alzheimer's Disease Classification
Moritz Boehle et al.
FRONTIERS IN AGING NEUROSCIENCE (2019)
VoxelMorph: A Learning Framework for Deformable Medical Image Registration
Guha Balakrishnan et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)
Identifying schizophrenia subgroups using clustering and supervised learning
Alexandra Talpalaru et al.
SCHIZOPHRENIA RESEARCH (2019)
Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data
Taeho Jo et al.
FRONTIERS IN AGING NEUROSCIENCE (2019)
Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation
Fabian Eitel et al.
NEUROIMAGE-CLINICAL (2019)
Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data
Weizheng Yan et al.
EBIOMEDICINE (2019)
Deep Neural Generative Model of Functional MRI Images for Psychiatric Disorder Diagnosis
Takashi Matsubara et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2019)
Spatio-temporal deep learning method for ADHD fMRI classification
Zhenyu Mao et al.
INFORMATION SCIENCES (2019)
Quantifying performance of machine learning methods for neuroimaging data
Lee Jollans et al.
NEUROIMAGE (2019)
Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization
Kanghan Oh et al.
SCHIZOPHRENIA RESEARCH (2019)
Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large-scale multi-sample study
Walter H. L. Pinaya et al.
HUMAN BRAIN MAPPING (2019)
Translational machine learning for psychiatric neuroimaging
Martin Walter et al.
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY (2019)
An overview of deep learning in medical imaging focusing on MRI
Alexander Selvikvag Lundervold et al.
ZEITSCHRIFT FUR MEDIZINISCHE PHYSIK (2019)
Machine learning techniques in a structural and functional MRI diagnostic approach in schizophrenia: a systematic review
Renato de Filippis et al.
NEUROPSYCHIATRIC DISEASE AND TREATMENT (2019)
Resting state connectivity best predicts alcohol use severity in moderate to heavy alcohol users
Samantha J. Fede et al.
NEUROIMAGE-CLINICAL (2019)
Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling
Shui-Hua Wang et al.
JOURNAL OF MEDICAL SYSTEMS (2018)
Brain age predicts mortality
J. H. Cole et al.
MOLECULAR PSYCHIATRY (2018)
Cross-validation failure: Small sample sizes lead to large error bars
Gael Varoquaux
NEUROIMAGE (2018)
SMRI Biomarkers Predict Electroconvulsive Treatment Outcomes: Accuracy with Independent Data Sets
Rongtao Jiang et al.
NEUROPSYCHOPHARMACOLOGY (2018)
Decoding diagnosis and lifetime consumption in alcohol dependence from grey-matter pattern information
M. Guggenmos et al.
ACTA PSYCHIATRICA SCANDINAVICA (2018)
Cortical and Subcortical Brain Morphometry Differences Between Patients With Autism Spectrum Disorder and Healthy Individuals Across the Lifespan: Results From the ENIGMA ASD Working Group
Daan van Rooij et al.
AMERICAN JOURNAL OF PSYCHIATRY (2018)
Machine Learning Approaches for Clinical Psychology and Psychiatry
Dominic B. Dwyer et al.
Annual Review of Clinical Psychology (2018)
Resting state functional connectivity of the amygdala and problem drinking in non-dependent alcohol drinkers
Sien Hu et al.
DRUG AND ALCOHOL DEPENDENCE (2018)
Alzheimer's disease diagnostics by a 3D deeply supervised adaptable convolutional network
Ehsan Hosseini Asl et al.
FRONTIERS IN BIOSCIENCE-LANDMARK (2018)
Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review
Cao Xiao et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2018)
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease
Sarah Parisot et al.
MEDICAL IMAGE ANALYSIS (2018)
POINTS OF SIGNIFICANCE Statistics versus machine learning
Danilo Bzdok et al.
NATURE METHODS (2018)
The current role of MRI in differentiating multiple sclerosis from its imaging mimics
Ruth Geraldes et al.
NATURE REVIEWS NEUROLOGY (2018)
Random forest based classification of alcohol dependence patients and healthy controls using resting state MRI
Xi Zhu et al.
NEUROSCIENCE LETTERS (2018)
Identification of autism spectrum disorder using deep learning and the ABIDE dataset
Anibal Solon Heinsfeld et al.
NEUROIMAGE-CLINICAL (2018)
Classification of multi-site MR images in the presence of heterogeneity using multi-task learning
Qiongmin Ma et al.
NEUROIMAGE-CLINICAL (2018)
Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI
Ling-Li Zeng et al.
EBIOMEDICINE (2018)
Machine learning in major depression: From classification to treatment outcome prediction
Shuang Gao et al.
CNS NEUROSCIENCE & THERAPEUTICS (2018)
Automated Classification of Skin Lesions: From Pixels to Practice
Akhila Narla et al.
JOURNAL OF INVESTIGATIVE DERMATOLOGY (2018)
Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia
Sergey M. Plis et al.
NEUROIMAGE (2018)
Prediction Models of Functional Outcomes for Individuals in the Clinical High-Risk State for Psychosis or With Recent-Onset Depression A Multimodal, Multisite Machine Learning Analysis
Nikolaos Koutsouleris et al.
JAMA PSYCHIATRY (2018)
Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging
Yuhui Du et al.
FRONTIERS IN NEUROSCIENCE (2018)
Structural neuroimaging as clinical predictor: A review of machine learning applications
Jose Maria Mateos-Perez et al.
NEUROIMAGE-CLINICAL (2018)
Disrupted Brain Network Efficiency and Decreased Functional Connectivity in Multi-sensory Modality Regions in Male Patients With Alcohol Use Disorder
Yaqi Wang et al.
FRONTIERS IN HUMAN NEUROSCIENCE (2018)
Mapping the Heterogeneous Phenotype of Schizophrenia and Bipolar Disorder Using Normative Models
Thomas Wolfers et al.
JAMA PSYCHIATRY (2018)
Resting-state connectivity biomarkers define neurophysiological subtypes of depression
Andrew T. Drysdale et al.
NATURE MEDICINE (2017)
Geometric Deep Learning Going beyond Euclidean data
Michael M. Bronstein et al.
IEEE SIGNAL PROCESSING MAGAZINE (2017)
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth
Vanya V. Valindria et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2017)
Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions
Zeynettin Akkus et al.
JOURNAL OF DIGITAL IMAGING (2017)
A survey on deep learning in medical image analysis
Geert Litjens et al.
MEDICAL IMAGE ANALYSIS (2017)
Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva et al.
NATURE (2017)
Building better biomarkers: brain models in translational neuroimaging
Choong-Wan Woo et al.
NATURE NEUROSCIENCE (2017)
Predictive modelling using neuroimaging data in the presence of confounds
Anil Rao et al.
NEUROIMAGE (2017)
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
James H. Cole et al.
NEUROIMAGE (2017)
Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines
Gael Varoquaux et al.
NEUROIMAGE (2017)
BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment
Jeremy Kawahara et al.
NEUROIMAGE (2017)
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls
Mohammad R. Arbabshirani et al.
NEUROIMAGE (2017)
Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications
Sandra Vieira et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2017)
Sample composition alters associations between age and brain structure
Kaja Z. LeWinn et al.
NATURE COMMUNICATIONS (2017)
Neural Predictors of Initiating Alcohol Use During Adolescence
Lindsay M. Squeglia et al.
AMERICAN JOURNAL OF PSYCHIATRY (2017)
Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group
L. Schmaal et al.
MOLECULAR PSYCHIATRY (2016)
Understanding Heterogeneity in Clinical Cohorts Using Normative Models: Beyond Case-Control Studies
Andre F. Marquand et al.
BIOLOGICAL PSYCHIATRY (2016)
Cognitive biases associated with medical decisions: a systematic review
Gustavo Saposnik et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2016)
White matter hyperintensities and imaging patterns of brain ageing in the general population
Mohamad Habes et al.
BRAIN (2016)
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
Varun Gulshan et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2016)
Can we open the black box of AI?
Davide Castelvecchi
NATURE (2016)
The search for imaging biomarkers in psychiatric disorders
Anissa Abi-Dargham et al.
NATURE MEDICINE (2016)
Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia
Junghoe Kim et al.
NEUROIMAGE (2016)
Neurobiological markers predicting treatment response in anxiety disorders: A systematic review and implications for clinical application
Ulrike Lueken et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2016)
Predicting the Future - Big Data, Machine Learning, and Clinical Medicine
Ziad Obermeyer et al.
NEW ENGLAND JOURNAL OF MEDICINE (2016)
Psychoradiology: The Frontier of Neuroimaging in Psychiatry
Su Lui et al.
RADIOLOGY (2016)
A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets
Sandeep R. Panta et al.
FRONTIERS IN NEUROINFORMATICS (2016)
Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters
Hugo G. Schnack et al.
FRONTIERS IN PSYCHIATRY (2016)
Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia
Walter H. L. Pinaya et al.
SCIENTIFIC REPORTS (2016)
Predicting the future relapse of alcohol-dependent patients from structural and functional brain images
Sambu Seo et al.
ADDICTION BIOLOGY (2015)
Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease
Siqi Liu et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2015)
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2015)
Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction
Meenal J. Patel et al.
INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY (2015)
Machine learning applications in genetics and genomics
Maxwell W. Libbrecht et al.
NATURE REVIEWS GENETICS (2015)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics
Thomas Wolfers et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2015)
Brain disorders? Precisely
Thomas R. Insel et al.
SCIENCE (2015)
Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data
Gopikrishna Deshpande et al.
IEEE TRANSACTIONS ON CYBERNETICS (2015)
Identification of a Common Neurobiological Substrate for Mental Illness
Madeleine Goodkind et al.
JAMA PSYCHIATRY (2015)
On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
Sebastian Bach et al.
PLOS ONE (2015)
Neuropsychosocial profiles of current and future adolescent alcohol misusers
Robert Whelan et al.
NATURE (2014)
On the interpretation of weight vectors of linear models in multivariate neuroimaging
Stefan Haufe et al.
NEUROIMAGE (2014)
Correction of inter-scanner and within-subject variance in structural MRI based automated diagnosing
Daniel Kostro et al.
NEUROIMAGE (2014)
Can structural MRI aid in clinical classification? A machine learning study in two independent samples of patients with schizophrenia, bipolar disorder and healthy subjects
Hugo G. Schnack et al.
NEUROIMAGE (2014)
Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
Heung-Il Suk et al.
NEUROIMAGE (2014)
Brain grey matter abnormalities in medication-free patients with major depressive disorder: a meta-analysis
Y-J Zhao et al.
PSYCHOLOGICAL MEDICINE (2014)
Bipolar and Schizophrenia Network for Intermediate Phenotypes: Outcomes Across the Psychosis Continuum
Carol A. Tamminga et al.
SCHIZOPHRENIA BULLETIN (2014)
Subtyping Attention-Deficit/Hyperactivity Disorder Using Temperament Dimensions Toward Biologically Based Nosologic Criteria
Sarah L. Karalunas et al.
JAMA PSYCHIATRY (2014)
Deep learning for neuroimaging: a validation study
Sergey M. Plis et al.
FRONTIERS IN NEUROSCIENCE (2014)
Multivariate neuroanatomical classification of cognitive subtypes in schizophrenia: A support vector machine learning approach
Ian C. Gould et al.
NEUROIMAGE-CLINICAL (2014)
The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception
Michael W. Weiner et al.
Alzheimers & Dementia (2013)
Toward the future of psychiatric diagnosis: the seven pillars of RDoC
Bruce N. Cuthbert et al.
BMC MEDICINE (2013)
Neuroimaging-Based Biomarkers in Psychiatry: Clinical Opportunities of a Paradigm Shift
Cynthia H. V. Fu et al.
CANADIAN JOURNAL OF PSYCHIATRY-REVUE CANADIENNE DE PSYCHIATRIE (2013)
NEUROBIOLOGY OF ANXIOUS DEPRESSION: A REVIEW
Dawn F. Ionescu et al.
DEPRESSION AND ANXIETY (2013)
The common dementias: a pictorial review
Pervinder Bhogal et al.
EUROPEAN RADIOLOGY (2013)
Representation Learning: A Review and New Perspectives
Yoshua Bengio et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2013)
Confounds in multivariate pattern analysis: Theory and rule representation case study
Michael T. Todd et al.
NEUROIMAGE (2013)
Using genetic, cognitive and multi-modal neuroimaging data to identify ultra-high-risk and first-episode psychosis at the individual level
W. Pettersson-Yeo et al.
PSYCHOLOGICAL MEDICINE (2013)
fMRI pattern recognition in obsessive-compulsive disorder
Martin Weygandt et al.
NEUROIMAGE (2012)
Diagnostic neuroimaging across diseases
Stefan Kloeppel et al.
NEUROIMAGE (2012)
Neurocircuitry models of posttraumatic stress disorder and beyond: A meta-analysis of functional neuroimaging studies
Ronak Patel et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2012)
Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review
Graziella Orru et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2012)
Using Multivariate Machine Learning Methods and Structural MRI to Classify Childhood Onset Schizophrenia and Healthy Controls
Deanna Greenstein et al.
Frontiers in Psychiatry (2012)
ADHD-200 Global Competition: diagnosing ADHD using personal characteristic data can outperform resting state fMRI measurements
Matthew R. G. Brown et al.
FRONTIERS IN SYSTEMS NEUROSCIENCE (2012)
Alcohol and the Human Brain: A Systematic Review of Different Neuroimaging Methods
Mira Buehler et al.
ALCOHOLISM-CLINICAL AND EXPERIMENTAL RESEARCH (2011)
Overview of Functional Magnetic Resonance Imaging
Gary H. Glover
NEUROSURGERY CLINICS OF NORTH AMERICA (2011)
MRI Pattern Recognition in Multiple Sclerosis Normal-Appearing Brain Areas
Martin Weygandt et al.
PLOS ONE (2011)
Age Correction in Dementia - Matching to a Healthy Brain
Juergen Dukart et al.
PLOS ONE (2011)
Research Domain Criteria (RDoC): Toward a New Classification Framework for Research on Mental Disorders
Thomas Insel et al.
AMERICAN JOURNAL OF PSYCHIATRY (2010)
Evidence-based guideline: The role of diffusion and perfusion MRI for the diagnosis of acute ischemic stroke Report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology
P. D. Schellinger et al.
NEUROLOGY (2010)
Self-reflection and the brain: A theoretical review and meta-analysis of neuroimaging studies with implications for schizophrenia
Lisette van der Meer et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2010)
A systematic review of the effects of antipsychotic drugs on brain volume
J. Moncrieff et al.
PSYCHOLOGICAL MEDICINE (2010)
Use of Neuroanatomical Pattern Classification to Identify Subjects in At-Risk Mental States of Psychosis and Predict Disease Transition
Nikolaos Koutsouleris et al.
ARCHIVES OF GENERAL PSYCHIATRY (2009)
Longitudinal progression of Alzheimers-like patterns of atrophy in normal older adults: the SPARE-AD index
Christos Davatzikos et al.
BRAIN (2009)
Circular analysis in systems neuroscience: the dangers of double dipping
Nikolaus Kriegeskorte et al.
NATURE NEUROSCIENCE (2009)
Accuracy of dementia diagnosisa direct comparison between radiologists and a computerized method
Stefan Kloeppel et al.
BRAIN (2008)
Automatic classification of MR scans in Alzheimers disease
Stefan Kloeppel et al.
BRAIN (2008)
Depression, anxiety and somatization in primary care:: syndrome overlap and functional impairment
Bernd Loewe et al.
GENERAL HOSPITAL PSYCHIATRY (2008)
The intrinsic functional organization of the brain is altered in autism
Daniel P. Kennedy et al.
NEUROIMAGE (2008)
Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI
Zang Yu-Feng et al.
BRAIN & DEVELOPMENT (2007)
Brain morphometry and cognitive performance in detoxified alcohol-dependents with preserved psychosocial functioning
Sandra Chanraud et al.
NEUROPSYCHOPHARMACOLOGY (2007)
Bias in error estimation when using cross-validation for model selection
S Varma et al.
BMC BIOINFORMATICS (2006)
Structural brain imaging of attention-deficit/hyperactivity disorder
LJ Seidman et al.
BIOLOGICAL PSYCHIATRY (2005)
Abnormal gyral complexity in first-episode schizophrenia
KL Narr et al.
BIOLOGICAL PSYCHIATRY (2004)
Canonical correlation analysis: An overview with application to learning methods
DR Hardoon et al.
NEURAL COMPUTATION (2004)
A review of MRI findings in schizophrenia
ME Shenton et al.
SCHIZOPHRENIA RESEARCH (2001)
Share Paper
