What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Internal medicine
His primary areas of investigation include Neuroscience, Artificial intelligence, Magnetic resonance imaging, Human brain and Pattern recognition.
In his study, which falls under the umbrella issue of Neuroscience, Functional imaging is strongly linked to Stereotaxic technique.
The study of Artificial intelligence is intertwined with the study of Computer vision in a number of ways.
His study in Magnetic resonance imaging is interdisciplinary in nature, drawing from both Temporal lobe, Neuroimaging and Brain development.
His Human brain study combines topics in areas such as Somatosensory system, Corpus callosum, Functional magnetic resonance imaging, Brain activity and meditation and Cingulate sulcus.
His Pattern recognition research includes themes of Maxima and minima, Coordinate system, Surface reconstruction, Random field and Atlas.
His most cited work include:
- Brain development during childhood and adolescence: a longitudinal MRI study. (4199 citations)
- A nonparametric method for automatic correction of intensity nonuniformity in MRI data (3786 citations)
- Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space (2930 citations)
What are the main themes of his work throughout his whole career to date?
Neuroscience, Artificial intelligence, Magnetic resonance imaging, Pattern recognition and Human brain are his primary areas of study.
His Neuroscience study frequently draws connections between related disciplines such as Cerebral blood flow.
Alan C. Evans combines subjects such as Machine learning and Computer vision with his study of Artificial intelligence.
The various areas that he examines in his Magnetic resonance imaging study include Positron emission tomography, Nuclear medicine and Pathology.
Cerebral cortex is frequently linked to Cortex in his study.
Cognition and Audiology are commonly linked in his work.
He most often published in these fields:
- Neuroscience (31.06%)
- Artificial intelligence (19.07%)
- Magnetic resonance imaging (12.88%)
What were the highlights of his more recent work (between 2017-2021)?
- Neuroscience (31.06%)
- Neuroimaging (9.60%)
- Artificial intelligence (19.07%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Neuroscience, Neuroimaging, Artificial intelligence, Cognition and Disease.
His research in Neuroscience tackles topics such as Autism which are related to areas like Functional connectivity.
His Neuroimaging research is multidisciplinary, incorporating perspectives in White matter, Sample, Macaque and Brain development.
The study incorporates disciplines such as Machine learning, Computer vision and Pattern recognition in addition to Artificial intelligence.
His work carried out in the field of Pattern recognition brings together such families of science as Voxel and Diffusion MRI.
As part of one scientific family, Alan C. Evans deals mainly with the area of Cognition, narrowing it down to issues related to the Audiology, and often Autism spectrum disorder, Electroencephalography, Magnetic resonance imaging, First episode psychosis and First episode.
Between 2017 and 2021, his most popular works were:
- Neuroanatomical differences in obesity: meta-analytic findings and their validation in an independent dataset. (47 citations)
- Mapping Cortical Laminar Structure in the 3D BigBrain. (44 citations)
- Restricted and Repetitive Behavior and Brain Functional Connectivity in Infants at Risk for Developing Autism Spectrum Disorder. (25 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Internal medicine
Alan C. Evans spends much of his time researching Neuroimaging, Cognition, Neuroscience, Cohort and Cerebral cortex.
His studies deal with areas such as White matter, Prefrontal cortex, Clinical psychology and Motion as well as Neuroimaging.
Within one scientific family, he focuses on topics pertaining to Body mass index under Prefrontal cortex, and may sometimes address concerns connected to Brain mapping.
His Cognition study integrates concerns from other disciplines, such as Alzheimer's disease, Contrast, Early psychosis and Audiology.
His studies link Schizophrenia with Neuroscience.
His Cerebral cortex research is multidisciplinary, incorporating elements of Magnetic resonance imaging and Convolutional neural network.
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