What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Machine learning
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 most cited work include:
- Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review (635 citations)
- Describing the Brain in Autism in Five Dimensions—Magnetic Resonance Imaging-Assisted Diagnosis of Autism Spectrum Disorder Using a Multiparameter Classification Approach (311 citations)
- Investigating the predictive value of whole-brain structural MR scans in autism: A pattern classification approach (307 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Artificial intelligence (46.74%)
- Neuroimaging (44.57%)
- Machine learning (31.52%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (46.74%)
- Neuroimaging (44.57%)
- Machine learning (31.52%)
In recent papers he was focusing on the following fields of study:
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.
Between 2019 and 2021, his most popular works were:
- The genetic architecture of the human cerebral cortex. (116 citations)
- Individual differences v. the average patient: mapping the heterogeneity in ADHD using normative models. (32 citations)
- Individual differences v. the average patient: mapping the heterogeneity in ADHD using normative models. (32 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Machine learning
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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