What is he best known for?
The fields of study he is best known for:
- Statistics
- Internal medicine
- Normal distribution
His primary scientific interests are in Artificial intelligence, Pattern recognition, Neuroscience, Statistics and Magnetic resonance imaging.
His Voxel study in the realm of Artificial intelligence interacts with subjects such as Statistical analysis.
His research integrates issues of White matter and Anatomy in his study of Neuroscience.
His Autoregressive model and Linear model study, which is part of a larger body of work in Statistics, is frequently linked to Sensitivity and Expectation–maximization algorithm, bridging the gap between disciplines.
His Linear model research is multidisciplinary, incorporating perspectives in Analysis of covariance, Statistical parameter, Statistical model, Applied mathematics and Statistical parametric mapping.
As part of the same scientific family, Keith J. Worsley usually focuses on Magnetic resonance imaging, concentrating on Positron emission tomography and intersecting with Tomography and Pathology.
His most cited work include:
- Statistical parametric maps in functional imaging: A general linear approach (8428 citations)
- A unified statistical approach for determining significant signals in images of cerebral activation. (2310 citations)
- Analysis of fMRI time-series revisited--again. (1908 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Random field, Artificial intelligence, Pattern recognition, Statistics and Neuroscience.
His Random field study incorporates themes from Statistical hypothesis testing, Geometry and Mathematical analysis, Euler characteristic.
Keith J. Worsley usually deals with Artificial intelligence and limits it to topics linked to Brain mapping and White matter.
His research investigates the connection between Pattern recognition and topics such as Maxima and minima that intersect with issues in Parametric statistics.
His biological study spans a wide range of topics, including Anatomy and Pathology.
His Linear model research incorporates themes from Algorithm and Multivariate statistics.
He most often published in these fields:
- Random field (29.45%)
- Artificial intelligence (28.08%)
- Pattern recognition (23.29%)
What were the highlights of his more recent work (between 2007-2014)?
- Random field (29.45%)
- Neuroscience (19.18%)
- Pathology (13.70%)
In recent papers he was focusing on the following fields of study:
Keith J. Worsley focuses on Random field, Neuroscience, Pathology, Epilepsy and Statistical hypothesis testing.
Keith J. Worsley has included themes like Euler characteristic, Applied mathematics and Multivariate random variable in his Random field study.
His Applied mathematics research focuses on subjects like Statistics, which are linked to Multilinear map.
Keith J. Worsley combines subjects such as White matter, Grey matter, Hyperintensity and Brain mapping with his study of Pathology.
The Multiple comparisons problem study combines topics in areas such as Artificial intelligence and Pattern recognition.
His work deals with themes such as Amygdala, Linear model, Computer vision and Brain size, which intersect with Artificial intelligence.
Between 2007 and 2014, his most popular works were:
- Guidelines for reporting an fMRI study (376 citations)
- Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load. (337 citations)
- Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load. (337 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Internal medicine
- Normal distribution
Keith J. Worsley mostly deals with Neuroscience, Pathology, Cerebral cortex, Epilepsy and Atrophy.
His work carried out in the field of Pathology brings together such families of science as Precentral gyrus, White matter, Grey matter and Hyperintensity.
His Cerebral cortex study integrates concerns from other disciplines, such as Central nervous system disease, Surgery, Brain damage and Brain mapping.
His work on Temporal lobe and Idiopathic generalized epilepsy as part of general Epilepsy research is often related to Thalamo cortical and In patient, thus linking different fields of science.
The various areas that he examines in his Temporal lobe study include Pathological, Neocortex, Anatomy and Hippocampal formation, Entorhinal cortex.
His Atrophy study combines topics in areas such as Young adult, Generalized seizure, Epileptic activity and Cardiology.
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