ReviewJournal of epilepsy research2020
Artificial Intelligence and Computational Approaches for Epilepsy.
Review in Journal of epilepsy research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 70 citations in OpenAlex.
- Medical Technology: A Systematic Review on Medical Devices Utilized for Epilepsy Prediction and Management.Current neuropharmacology · 2022Pooled it
- A structured narrative review on VNS-treated drug-resistant epilepsy: EEG markers, neurochemical mechanisms, and future biomarker-driven computational directions.Frontiers in neuroscience · 2026Review
- From theory to therapy: integrating artificial intelligence for transformative healthcare innovation.Health systems (Basingstoke, England) · 2026Article
- Symptom network analysis of prefrontal seizures.Epilepsia · 2025Article
- Assistive Artificial Intelligence in Epilepsy and Its Impact on Epilepsy Care in Low- and Middle-Income Countries.Brain sciences · 2025Review
- The Role of Artificial Intelligence in the Diagnosis and Management of Non-convulsive Seizures: A Narrative Review.Cureus · 2025Review
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- Localization of the epileptogenic network from scalp EEG using a patient-specific whole-brain model.Network neuroscience (Cambridge, Mass.) · 2025Article
- Unraveling the Mysteries of Alzheimer's Disease Using Artificial Intelligence.Reviews on recent clinical trials · 2025Review
- Neurostimulation for the Management of Epilepsy: Advances in Targeted Therapy.Current drug targets · 2025Review
- Home-Based sensing of the nervous system with clinical neurophysiology technologies: IFCN handbook chapter.Clinical neurophysiology practice · 2025Review
- Artificial Intelligence and Multiple Sclerosis.Current neurology and neuroscience reports · 2024Review
- A decision support system based on recurrent neural networks to predict medication dosage for patients with Parkinson's disease.Scientific reports · 2024Article
- Multiresolution directed transfer function approach for segment-wise seizure classification of epileptic EEG signal.Cognitive neurodynamics · 2024Article
- The predicative value of early quantitative electroencephalograph in epilepsy after severe traumatic brain injury in children.Frontiers in pediatrics · 2024Article
- The potential of large language model chatbots for application to epilepsy: Let's talk about physical exercise.Epilepsy & behavior reports · 2024Article
- Epilepsy classification using artificial intelligence: A web-based application.Epilepsia open · 2023Article
- Seizure onset zone identification using phase-amplitude coupling and multiple machine learning approaches for interictal electrocorticogram.Cognitive neurodynamics · 2023Article
- Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera.Epilepsy & behavior reports · 2023Article
- Temporal lobe epilepsy lateralisation and surgical outcome prediction using diffusion imaging.Journal of neurology, neurosurgery, and psychiatry · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Studies on treatment of epilepsy have been actively conducted in multiple avenues, but there are limitations in improving its efficacy due to between-subject variability in which treatment outcomes vary from patient to patient. Accordingly, there is a growing interest in precision medicine that provides accurate diagnosis for seizure types and optimal treatment for an individual epilepsy patient. Among these approaches, computational studies making this feasible are rapidly progressing in particular and have been widely applied in epilepsy. These computational studies are being conducted in two main streams: 1) artificial intelligence-based studies implementing computational machines with specific functions, such as automatic diagnosis and prognosis prediction for an individual patient, using machine learning techniques based on large amounts of data obtained from multiple patients and 2) patient-specific modeling-based studies implementing biophysical in-silico platforms to understand pathological mechanisms and derive the optimal treatment for each patient by reproducing the brain network dynamics of the particular patient per se based on individual patient's data. These computational approaches are important as it can integrate multiple types of data acquired from patients and analysis results into a single platform. If these kinds of methods are efficiently operated, it would suggest a novel paradigm for precision medicine.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.