SynthesisEpilepsia2023
Transforming epilepsy research: A systematic review on natural language processing applications.
Synthesis in Epilepsia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Transforming epilepsy research: A systematic review on natural language processing applications.Epilepsia · 2023Pooled it
- Modern generative large language models in epilepsy care: a scoping review of current applications, challenges, and future directions.Acta epileptologica · 2026Review
- [Structured Annotation and Information Extraction of Epilepsy Clinical Texts].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Article
- The limits of debiased clinical language models for cross-hospital generalization.Scientific reports · 2026Article
- Comparing three natural language processing methods for the automatic identification of epilepsy patients from French clinical notes.Epilepsia · 2026Article
- AI language model applications for early diagnosis of childhood epilepsy based on unstructured first-visit patient narratives: A cohort study.Epileptic disorders : international epilepsy journal with videotape · 2025Article
- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
- Extracting epilepsy-related information from unstructured clinic letters using large language models.Epilepsia · 2025Article
- Leveraging pretrained language models for seizure frequency extraction from epilepsy evaluation reports.NPJ digital medicine · 2025Article
- Evaluating GPT Models for Automated Literature Screening in Wastewater-Based Epidemiology.ACS environmental Au · 2025Article
- Data transformation of unstructured electroencephalography reports by natural language processing: improving data usability for large-scale epilepsy studies.Frontiers in neurology · 2025Article
- Clinical signatures of genetic epilepsies precede diagnosis in electronic medical records of 32,000 individuals.Genetics in medicine : official journal of the American College of Medical Genetics · 2024Article
- Annotation of epilepsy clinic letters for natural language processing.Journal of biomedical semantics · 2024Article
- Natural Language Processing Applied to Spontaneous Recall of Famous Faces Reveals Memory Dysfunction in Temporal Lobe Epilepsy Patients.bioRxiv : the preprint server for biology · 2024Article
- Artificial intelligence in epilepsy - applications and pathways to the clinic.Nature reviews. Neurology · 2024Review
- Artificial Intelligence: Fundamentals and Breakthrough Applications in Epilepsy.Epilepsy currents · 2024Review
- Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study.JMIR formative research · 2024Article
- NLP-based tools for localization of the epileptogenic zone in patients with drug-resistant focal epilepsy.Scientific reports · 2024Article
- The potential of large language model chatbots for application to epilepsy: Let's talk about physical exercise.Epilepsy & behavior reports · 2024Article
- Large Language Models in Neurology Research and Future Practice.Neurology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Despite improved ancillary investigations in epilepsy care, patients' narratives remain indispensable for diagnosing and treatment monitoring. This wealth of information is typically stored in electronic health records and accumulated in medical journals in an unstructured manner, thereby restricting complete utilization in clinical decision-making. To this end, clinical researchers increasing apply natural language processing (NLP)-a branch of artificial intelligence-as it removes ambiguity, derives context, and imbues standardized meaning from free-narrative clinical texts. This systematic review presents an overview of the current NLP applications in epilepsy and discusses the opportunities and drawbacks of NLP alongside its future implications. We searched the PubMed and Embase databases with a "natural language processing" and "epilepsy" query (March 4, 2022) and included original research articles describing the application of NLP techniques for textual analysis in epilepsy. Twenty-six studies were included. Fifty-eight percent of these studies used NLP to classify clinical records into predefined categories, improving patient identification and treatment decisions. Other applications of NLP had structured clinical information retrieval from electronic health records, scientific papers, and online posts of patients. Challenges and opportunities of NLP applications for enhancing epilepsy care and research are discussed. The field could further benefit from NLP by replicating successes in other health care domains, such as NLP-aided quality evaluation for clinical decision-making, outcome prediction, and clinical record summarization.
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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.