Andre F. Marquand mostly deals with Neuroimaging, Neuroscience, Clinical psychology, Brain mapping and Psychiatry. His Neuroimaging research is multidisciplinary, incorporating perspectives in Pattern recognition, Facial expression, Artificial intelligence and Pattern recognition. In the subject of general Artificial intelligence, his work in Voxel is often linked to Toolbox, thereby combining diverse domains of study.
His work in the fields of Neuroscience, such as Brain asymmetry, overlaps with other areas such as Genome-wide association study. Andre F. Marquand has included themes like Serotonin reuptake inhibitor, Bipolar disorder and Reuptake inhibitor in his Clinical psychology study. His Psychiatry research includes elements of Alternative medicine, Disease mechanisms, Disease course and Set.
His primary areas of investigation include Artificial intelligence, Neuroimaging, Machine learning, Neuroscience and Clinical psychology. He interconnects Functional magnetic resonance imaging and Pattern recognition in the investigation of issues within Artificial intelligence. His study in the field of Functional neuroimaging also crosses realms of Modalities and Context.
The concepts of his Machine learning study are interwoven with issues in Covariance, Inference, Bayesian probability and Parametric statistics. In his study, Neuroanatomy is strongly linked to Autism spectrum disorder, which falls under the umbrella field of Neuroscience. His research in Clinical psychology intersects with topics in Healthy individuals, Schizophrenia and Major depressive disorder, Bipolar disorder, Depression.
Andre F. Marquand spends much of his time researching Artificial intelligence, Neuroimaging, Machine learning, Clinical psychology and Cognition. His studies in Artificial intelligence integrate themes in fields like Parametric statistics and Confounding. Andre F. Marquand conducted interdisciplinary study in his works that combined Neuroimaging and Intensity.
His Machine learning study incorporates themes from Motion, Functional magnetic resonance imaging and Bayesian probability. His Clinical psychology study combines topics from a wide range of disciplines, such as Healthy individuals and Autism. His study looks at the relationship between Attention deficit hyperactivity disorder and topics such as Cortex, which overlap with Brain mapping.
Andre F. Marquand mainly focuses on Cognition, Attention deficit hyperactivity disorder, Artificial intelligence, Machine learning and Genetic architecture. His biological study spans a wide range of topics, including Fractional anisotropy, Magnetic resonance imaging and Etiology. His Attention deficit hyperactivity disorder study is related to the wider topic of Clinical psychology.
The study incorporates disciplines such as Sampling and Sample size determination in addition to Artificial intelligence. His work on Support vector machine as part of his general Machine learning study is frequently connected to Face perception, thereby bridging the divide between different branches of science. His Brain mapping research is classified as research in Neuroscience.
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Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review
Graziella Orrù;William Pettersson-Yeo;Andre F. Marquand;Giuseppe Sartori.
Neuroscience & Biobehavioral Reviews (2012)
Investigating the predictive value of whole-brain structural MR scans in autism: A pattern classification approach
Christine Ecker;Vanessa Rocha-Rego;Patrick Johnston;Janaina Mourao-Miranda.
Describing the Brain in Autism in Five Dimensions—Magnetic Resonance Imaging-Assisted Diagnosis of Autism Spectrum Disorder Using a Multiparameter Classification Approach
Christine Ecker;Andre Marquand;Janaina Mourão-Miranda;Patrick Johnston.
The Journal of Neuroscience (2010)
PRoNTo: Pattern Recognition for Neuroimaging Toolbox
Jessica Schrouff;Maria Joao Rosa;Jane Rondina;Jane Rondina;Andre Marquand.
Pattern Classification of Sad Facial Processing : Toward the Development of Neurobiological Markers in Depression
Cynthia H.Y. Fu;Janaina Mourao-Miranda;Sergi G. Costafreda;Akash Khanna.
Biological Psychiatry (2008)
The genetic architecture of the human cerebral cortex
Katrina L. Grasby;Neda Jahanshad;Jodie N. Painter;Lucía Colodro-Conde.
Understanding Heterogeneity in Clinical Cohorts Using Normative Models: Beyond Case-Control Studies.
Andre F. Marquand;Andre F. Marquand;Iead Rezek;Jan Buitelaar;Christian F. Beckmann.
Biological Psychiatry (2016)
Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes.
Andre Marquand;Matthew Howard;Michael Brammer;Carlton Chu.
From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics
Thomas Wolfers;Jan K. Buitelaar;Christian F. Beckmann;Barbara Franke.
Neuroscience & Biobehavioral Reviews (2015)
Novel genetic loci associated with hippocampal volume
Derrek Hibar;Hieab H.H. Adams;Neda Jahanshad;Ganesh Chauhan.
Nature Communications (2017)
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