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Article

Decomposed FDG PET-based phenotypic heterogeneity predicting clinical prognosis and decision-making in temporal lobe epilepsy patients.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology - 1 Aug 2024

Guo Kun, Quan Zhiyong, Li Guiyu, Li Baojuan, Kang Fei, Wang Jing

Abstract excerpt

OBJECTIVE: This study utilized a data-driven Bayesian model to automatically identify distinct latent disease factors represented by overlapping glucose metabolism patterns from 18F-Fluorodeoxyglucose PET (18F-FDG PET) to analyze heterogeneity among patients with TLE. METHODS: We employed unsupervised machine learning to estimate latent disease factors from 18F-FDG PET scans, representing whole-brain glucose...

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Source

Identifiers

PMID: 38457084
DOI: 10.1007/s10072-024-07431-w

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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