What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Mutation
- Epilepsy
Epilepsy, Temporal lobe, Internal medicine, Ictal and Anesthesia are his primary areas of study.
His study with Epilepsy involves better knowledge in Neuroscience.
The Temporal lobe study combines topics in areas such as Recall, Frontal lobe, Neuropsychology and Audiology.
His Internal medicine study incorporates themes from Gastroenterology, Endocrinology and Mutation.
His Ictal research includes elements of Epileptogenesis and Radiology.
His Anesthesia study combines topics in areas such as Adverse effect and Carbamazepine.
His most cited work include:
- Mutations in GRIN2A cause idiopathic focal epilepsy with rolandic spikes (269 citations)
- Paroxysmal exercise-induced dyskinesia and epilepsy is due to mutations in SLC2A1, encoding the glucose transporter GLUT1. (262 citations)
- The use of SPECT and PET in routine clinical practice in epilepsy (111 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Epilepsy, Electroencephalography, Ictal, Artificial intelligence and Pattern recognition.
His Epilepsy research is multidisciplinary, incorporating elements of Internal medicine, Radiology and Pediatrics.
His research integrates issues of Anesthesia, Endocrinology, Gastroenterology and Cardiology in his study of Internal medicine.
Many of his research projects under Electroencephalography are closely connected to Sensitivity with Sensitivity, tying the diverse disciplines of science together.
The various areas that Wim Van Paesschen examines in his Ictal study include Single-photon emission computed tomography, EEG-fMRI and Perfusion.
The study incorporates disciplines such as Machine learning and Computer vision in addition to Artificial intelligence.
He most often published in these fields:
- Epilepsy (45.21%)
- Electroencephalography (22.34%)
- Ictal (21.81%)
What were the highlights of his more recent work (between 2018-2021)?
- Epilepsy (45.21%)
- Electroencephalography (22.34%)
- Artificial intelligence (19.15%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Epilepsy, Electroencephalography, Artificial intelligence, Pattern recognition and Ictal.
His Epilepsy research integrates issues from Odds ratio and Genetics.
His work focuses on many connections between Odds ratio and other disciplines, such as Placebo, that overlap with his field of interest in Internal medicine.
His study in Electroencephalography is interdisciplinary in nature, drawing from both Wearable technology and Multivariate statistics.
His Artificial intelligence study integrates concerns from other disciplines, such as Language mapping and Natural language processing.
He interconnects Transfer of learning, Machine learning, Support vector machine and Key in the investigation of issues within Ictal.
Between 2018 and 2021, his most popular works were:
- Diagnostic implications of genetic copy number variation in epilepsy plus (25 citations)
- Seizure outcome and use of antiepileptic drugs after epilepsy surgery according to histopathological diagnosis: a retrospective multicentre cohort study (21 citations)
- Clinical spectrum of STX1B-related epileptic disorders (20 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Mutation
- Artificial intelligence
Wim Van Paesschen focuses on Epilepsy, Ictal, Artificial intelligence, Temporal lobe and Electroencephalography.
His Epilepsy study frequently involves adjacent topics like Odds ratio.
His biological study spans a wide range of topics, including Transfer of learning, Machine learning and Support vector machine.
His Artificial intelligence research incorporates themes from Motor cortex, Transcranial magnetic stimulation, Key and Pattern recognition.
The concepts of his Temporal lobe study are interwoven with issues in Visual recognition, University hospital, Seizure detection and Audiology.
His Electroencephalography study combines topics from a wide range of disciplines, such as Segmentation and Bold fmri.
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