ArticleNPJ precision oncology2024
Deep mutual learning on hybrid amino acid PET predicts H3K27M mutations in midline gliomas.
Article in NPJ precision oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Machine learning in neuroimaging for predicting H3K27M mutations in diffuse midline gliomas: a systematic review and meta-analysis.Frontiers in medicine · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Predicting H3K27M mutation status in midline gliomas non-invasively is of considerable interest, particularly using deep learning with 11C-methionine (MET) and 18F-fluoroethyltyrosine (FET) positron emission tomography (PET). To optimise prediction efficiency, we derived an assistance training (AT) scheme to allow mutual benefits between MET and FET learning to boost the predictability but still only require either PET as inputs for predictions. Our method significantly surpassed conventional convolutional neural network (CNN), radiomics-based, and MR-based methods, achieved an area under the curve (AUC) of 0.9343 for MET, and an AUC of 0.8619 for FET during internal cross-validation (n = 90). The performance remained high in hold-out testing (n = 19) and consecutive testing cohorts (n = 21), with AUCs of 0.9205 and 0.7404. The clinical feasibility of the proposed method was confirmed by the agreements to multi-departmental decisions and outcomes in pathology-uncertain cases. The findings positions our method as a promising tool for aiding treatment decisions in midline glioma.
Identifiers
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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.