Article in Radiology. Artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.
2 · The registry
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.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
9 authors.
Mustafa Ahmed MahmutogluFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).ORCID 0000-0002-4891-5547
Chandrakanth Jayachandran PreethaFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).ORCID 0000-0002-9875-1982
Hagen MeredigFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).ORCID 0009-0005-9177-4339
Joerg-Christian TonnFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).ORCID 0009-0004-1756-423X
Michael WellerFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).ORCID 0000-0002-1748-174X
Wolfgang WickFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).ORCID 0000-0002-6171-634X
Martin BendszusFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).
Gianluca BrugnaraFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).ORCID 0000-0003-2461-1407
Philipp VollmuthFrom the Department of Neuroradiology (M.A.M., C.J.P., H.M., M.B., G.B., P.V.), Department of Neuroradiology, Division for Computational Neuroimaging (M.A.M., C.J.P., H.M., G.B., P.V.), and Department of Neurology (W.W.), Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neurosurgery, University Hospital Munich LMU, Munich, Germany (J.C.T.); and Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland (M.W.).ORCID 0000-0002-6224-0064
Funding
No grant is acknowledged in the PubMed record.
6 · The paper itself
Abstract
Purpose To develop a fully automated device- and sequence-independent convolutional neural network (CNN) for reliable and high-throughput labeling of heterogeneous, unstructured MRI data. Materials and Methods Retrospective, multicentric brain MRI data (2179 patients with glioblastoma, 8544 examinations, 63 327 sequences) from 249 hospitals and 29 scanner types were used to develop a network based on ResNet-18 architecture to differentiate nine MRI sequence types, including T1-weighted, postcontrast T1-weighted, T2-weighted, fluid-attenuated inversion recovery, susceptibility-weighted, apparent diffusion coefficient, diffusion-weighted (low and high
Indexed as
Deep LearningBrainHumansMagnetic Resonance ImagingMulticenter Studies as TopicNeuroimagingRetrospective StudiesBrain/Brain StemCNSComputer Applications-General (Informatics)Convolutional Neural Network (CNN)Deep Learning AlgorithmsMachine Learning AlgorithmsMR-ImagingNeural Networks
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.
Deep Learning-based Identification of Brain MRI Sequences Using a Model Trained on Large Multicentric Study Cohorts. · full record | OpenQuestion