What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Artificial intelligence
- Statistics
Martin Styner spends much of his time researching Neuroimaging, Artificial intelligence, Neuroscience, Diffusion MRI and White matter.
His Neuroimaging study integrates concerns from other disciplines, such as Autism, Autism spectrum disorder, Human Connectome Project, Physiology and Resting State Functional Connectivity MRI.
His Artificial intelligence research integrates issues from Machine learning, Computer vision and Pattern recognition.
His work carried out in the field of Neuroscience brings together such families of science as Endocrinology, Internal medicine and Brain size.
His Diffusion MRI research is included under the broader classification of Magnetic resonance imaging.
Martin Styner combines subjects such as Anatomy, Viral shedding and Brain mapping with his study of White matter.
His most cited work include:
- Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets (698 citations)
- Early brain development in infants at high risk for autism spectrum disorder (461 citations)
- Differences in white matter fiber tract development present from 6 to 24 months in infants with autism. (456 citations)
What are the main themes of his work throughout his whole career to date?
Martin Styner mainly focuses on Artificial intelligence, Pattern recognition, Computer vision, Diffusion MRI and White matter.
His research brings together the fields of Neuroimaging and Artificial intelligence.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Geodesic, Data mining and Atlas.
His Diffusion MRI research includes themes of Atlas and Statistics.
His work deals with themes such as Corpus callosum, Neuroscience, Pediatrics and Brain size, which intersect with White matter.
The study incorporates disciplines such as Internal medicine and Pathology in addition to Magnetic resonance imaging.
He most often published in these fields:
- Artificial intelligence (34.75%)
- Pattern recognition (18.38%)
- Computer vision (17.58%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (34.75%)
- White matter (15.56%)
- Neuroimaging (13.94%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, White matter, Neuroimaging, Pattern recognition and Neuroscience are his primary areas of study.
His Deep learning, Segmentation and Discriminative model study in the realm of Artificial intelligence connects with subjects such as Set.
His research integrates issues of Diffusion MRI, Pediatrics and Audiology in his study of White matter.
His Neuroimaging study incorporates themes from Extra axial, Cognition, Internal medicine, Human brain and Physiology.
His research investigates the connection with Pattern recognition and areas like Artificial neural network which intersect with concerns in Classifier and Temporomandibular joint.
His Neuroscience study combines topics from a wide range of disciplines, such as Neurodegeneration and Immune activation.
Between 2017 and 2021, his most popular works were:
- Infant gut microbiome associated with cognitive Development (147 citations)
- Maternal Systemic Interleukin-6 During Pregnancy Is Associated With Newborn Amygdala Phenotypes and Subsequent Behavior at 2 Years of Age (105 citations)
- The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development. (93 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Artificial intelligence
- Statistics
His primary areas of investigation include Cognition, Neuroimaging, Artificial intelligence, Developmental psychology and Cognitive development.
His study in Neuroimaging is interdisciplinary in nature, drawing from both Connectome, Physiology, Audiology and Brain development.
His studies deal with areas such as Machine learning, Wavefront, Geodesic and Pattern recognition as well as Artificial intelligence.
His Developmental psychology research incorporates themes from Fractional anisotropy, Gestational age and Gut microbiome.
His studies in Cognitive development integrate themes in fields like White matter, Gut flora, Effects of sleep deprivation on cognitive performance, Cortex and Animal data.
His White matter research is multidisciplinary, incorporating perspectives in Prenatal care, Diffusion MRI, Depression, Pediatrics and Brain mapping.
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