article Open AccessTop 1% cited
Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI
European Radiology · 2019 · Vol. 29(7) · pp. 3338–3347
Charlie Alexander Hamm✉(Yale University)Clinton J. Wang(Yale University)Lynn Jeanette Savic(Yale University)Marc Ferrante(Yale University)Isabel Schobert(Humboldt-Universität zu Berlin)Todd Schlachter(Yale University)MingDe Lin(Yale University)James S. Duncan(Yale University)Jeffrey C. Weinreb(Yale University)Julius Chapiro(Yale University)Brian Letzen(Yale University)
Radiomics and Machine Learning in Medical ImagingLiver Disease Diagnosis and TreatmentHepatocellular Carcinoma Treatment and PrognosisConvolutional neural networkMedicineNeuroradiologyRadiologyMagnetic resonance imagingDeep learningClassifier (UML)Artificial intelligenceInterventional radiologyUltrasound
MeSH terms
Deep LearningAdultAgedBile Duct NeoplasmsBile Ducts, IntrahepaticFemaleCarcinoma, HepatocellularHumansImage Interpretation, Computer-AssistedLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedROC CurveSensitivity and Specificity
Funding
- RSNA Research and Education Foundation
- National Cancer Institute
Citations
335
FWCI
26.65
field-weighted impact
References
25
Percentile
100%
vs. same field & year
Citations per year
References
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The Lancet · 2016 · 6,646 citations
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
PLoS Medicine · 2018 · 1,330 citations
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