ArticleNature communications2024
Identification of four biotypes in temporal lobe epilepsy via machine learning on brain images.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- Imaging insights into temporal lobe epilepsy: an AES-SDM meta-analysis and retrospective cohort study.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Pooled it
- Real-World Imaging Data: Opportunities and Challenges.JMIR medical informatics · 2026Article
- AI in epilepsy neuroimaging.Current opinion in neurology · 2026Review
- Mapping Individualized Dual-Axis Network Topology in Focal Epilepsy: Divergent Alterations in System Integrity, Integration, and Clinical Correlates.bioRxiv : the preprint server for biology · 2026Article
- Review
- Development and validation of interpretable multimodal clinical-radiomics models for predicting epileptogenic foci and surgical outcomes in tuberous sclerosis complex: A multicenter study.PLOS digital health · 2026Article
- Seizures beget more than seizures: Understanding the cellular, structural, individual and societal impact of seizures in epilepsy.Epilepsia open · 2025Review
- Personalized biomarkers of multiscale functional alterations in temporal lobe epilepsy.Nature communications · 2025Article
- Stronger pre-surgical functional connectivity networks are associated with improved surgical outcome in temporal lobe epilepsy.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025Article
- Multimodal quantitative analysis guides precise preoperative localization of epilepsy.Journal of neurology · 2025Review
- Elucidating Development Trajectories of Brain Functional Abnormalities in Major Depressive Disorder Utilizing a Data-Driven Disease Progression Model.Human brain mapping · 2025Article
- Identifying brain degeneration patterns in early-stage Parkinson's disease: a multimodal MRI study.NPJ Parkinson's disease · 2025Article
- Alternations in morphometric similarity network in mesial temporal epilepsy correlate to neuroinflammatory pathway gene transcriptions.Acta epileptologica · 2025Article
- Temporal Lobe Epilepsy Perturbs the Brain-Wide Excitation-Inhibition Balance: Associations with Microcircuit Organization, Clinical Parameters, and Cognitive Dysfunction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Progressive brain atrophy and cortical reorganization related to surgery in temporal lobe epilepsy.Annals of clinical and translational neurology · 2025Article
- Temporopolar blurring signifies abnormalities of white matter in mesial temporal lobe epilepsy.Annals of clinical and translational neurology · 2024Article
- Estimated Disease Progression Trajectory of White Matter Disruption in Unilateral Temporal Lobe Epilepsy: A Data-Driven Machine Learning Approach.Brain sciences · 2024Article
- Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm.Nature communications · 2024Article
- Predicting the Path: How Machine Learning Can Identify Subtypes of Epilepsy and Predict Disease Progression.Epilepsy currentsArticle
- Astrocyte-derived stanniocalcin-1 orchestrates epileptogenesis through NF-κB-dependent neuroinflammation.Cell cycle (Georgetown, Tex.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence provides an opportunity to try to redefine disease subtypes based on similar pathobiology. Using a machine-learning algorithm (Subtype and Stage Inference) with cross-sectional MRI from 296 individuals with focal epilepsy originating from the temporal lobe (TLE) and 91 healthy controls, we show phenotypic heterogeneity in the pathophysiological progression of TLE. This study was registered in the Chinese Clinical Trials Registry (number: ChiCTR2200062562). We identify two hippocampus-predominant phenotypes, characterized by atrophy beginning in the left or right hippocampus; a third cortex-predominant phenotype, characterized by hippocampus atrophy after the neocortex; and a fourth phenotype without atrophy but amygdala enlargement. These four subtypes are replicated in the independent validation cohort (109 individuals). These subtypes show differences in neuroanatomical signature, disease progression and epilepsy characteristics. Five-year follow-up observations of these individuals reveal differential seizure outcomes among subtypes, indicating that specific subtypes may benefit from temporal surgery or pharmacological treatment. These findings suggest a diverse pathobiological basis underlying focal epilepsy that potentially yields to stratification and prognostication - a necessary step for precise 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.