What is he best known for?
The fields of study he is best known for:
- Magnetic resonance imaging
- Neuroscience
- Internal medicine
N. Jon Shah spends much of his time researching Neuroscience, Functional magnetic resonance imaging, Audiology, Neural correlates of consciousness and Cognitive psychology.
His Neuroscience research is multidisciplinary, relying on both Huntington's disease, Voxel-based morphometry and Tourette syndrome.
His Functional magnetic resonance imaging study integrates concerns from other disciplines, such as Pattern recognition, Temporal lobe, Artificial intelligence and Auditory cortex.
His studies in Audiology integrate themes in fields like Psychosis, Diffusion MRI, Developmental psychology, Executive functions and Cohort.
His Neural correlates of consciousness research incorporates themes from Theory of mind and Perception.
His Cognitive psychology study frequently draws connections to other fields, such as Cognition.
His most cited work include:
- Polymodal Motion Processing in Posterior Parietal and Premotor Cortex: A Human fMRI Study Strongly Implies Equivalencies between Humans and Monkeys (704 citations)
- Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (493 citations)
- Recognition of emotional prosody and verbal components of spoken language: an fMRI study. (377 citations)
What are the main themes of his work throughout his whole career to date?
N. Jon Shah mainly focuses on Neuroscience, Nuclear magnetic resonance, Functional magnetic resonance imaging, Magnetic resonance imaging and Imaging phantom.
In his work, Psychosis is strongly intertwined with Schizophrenia, which is a subfield of Neuroscience.
In his research on the topic of Nuclear magnetic resonance, Kurtosis and Anisotropy is strongly related with Diffusion MRI.
His research integrates issues of Hippocampus, Audiology and Electroencephalography in his study of Functional magnetic resonance imaging.
His research investigates the connection with Magnetic resonance imaging and areas like Biomedical engineering which intersect with concerns in Neuroimaging.
His Neural correlates of consciousness research includes elements of Cognitive psychology and Functional imaging.
He most often published in these fields:
- Neuroscience (32.06%)
- Nuclear magnetic resonance (26.72%)
- Functional magnetic resonance imaging (23.92%)
What were the highlights of his more recent work (between 2017-2021)?
- Nuclear magnetic resonance (26.72%)
- Magnetic resonance imaging (21.12%)
- Artificial intelligence (14.25%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Nuclear magnetic resonance, Magnetic resonance imaging, Artificial intelligence, Positron emission tomography and Biomedical engineering.
His Nuclear magnetic resonance research incorporates elements of Blood flow, Parametric statistics, Glioma, Resting state fMRI and Spin echo.
His work carried out in the field of Magnetic resonance imaging brings together such families of science as Algorithm and Neuroscience.
In his study, N. Jon Shah carries out multidisciplinary Neuroscience and Calcium channel research.
His biological study spans a wide range of topics, including Machine learning, Computer vision and Pattern recognition.
His research investigates the link between Medical imaging and topics such as Biological neural network that cross with problems in Functional magnetic resonance imaging.
Between 2017 and 2021, his most popular works were:
- Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (493 citations)
- Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (41 citations)
- PET/MRI Radiomics in Patients With Brain Metastases (33 citations)
In his most recent research, the most cited papers focused on:
- Magnetic resonance imaging
- Neuroscience
- Internal medicine
His scientific interests lie mostly in Magnetic resonance imaging, Nuclear magnetic resonance, Positron emission tomography, Glioma and Artificial intelligence.
His work deals with themes such as Iterative reconstruction and Default mode network, which intersect with Magnetic resonance imaging.
His Nuclear magnetic resonance study combines topics in areas such as Quality, Image resolution, Parametric statistics and Aliasing.
His Positron emission tomography research integrates issues from Choline, Electroencephalography, Biopsy, Neuroimaging and Biomedical engineering.
His Glioma research also works with subjects such as
- Amino acid that connect with fields like Stereotactic biopsy,
- Brain tumor that intertwine with fields like Overall survival, Brain tumor segmentation, Diffusion MRI, Perfusion and Imaging modalities.
His studies deal with areas such as Encoder and Machine learning as well as Artificial intelligence.
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