Concepedia

Deep Learning Based on MR Imaging for Predicting Outcome of Uterine Fibroid Embolization

Yongheng Luo, I. Xi, Robin Wang, Hatem Omar Abdallah, Jing Wu, Ansar Z. Vance, Ken Chang, Maureen P. Kohi, Lisa P. Jones, Shilpa Reddy,

Journal of Vascular and Interventional Radiology · 2020 · 32 citations · 21 references

Concepts

MedicineGynecologyRadiologyDiagnostic ImagingDiagnostic RadiologyMachine LearningDeep LearningMagnetic Resonance Image ReconstructionMagnetic Resonance ImagingMagnetic Resonance Imaging PhysicsMedical ImagingUterine ImagingDeep Learning In RadiologyDeep Learning-based DiagnosisEmbolization ImagingFibroid CharacterizationUterine Fibroid EvaluationUterine Mass CharacterizationUterine Vascularity Assessment

References

21

Deep Residual Learning for Image Recognition

Kaiming He, Xiangyu Zhang, Shaoqing Ren et al. · 2016 · 222.1K citations · Full text

Computing, Computer Science, Computer Vision +11

Dermatologist-level classification of skin cancer with deep neural networks

Andre Esteva, Brett Kuprel, Roberto A. Novoa et al. · Nature · 2017 · 13.8K citations · Full text

Computing, Computer Science, Dermatology +16

TensorFlow: A system for large-scale machine learning

Martı́n Abadi, Paul Barham, Jianmin Chen et al. · arXiv (Cornell University) · 2016 · 8.8K citations · Full text

Computing, Computer Engineering, Computer Science +15

Approximate is Better than “Exact” for Interval Estimation of Binomial Proportions

Alan Agresti, Brent A. Coull · The American Statistician · 1998 · 3.2K citations

Natural Sciences, Biostatistics, Statistics +9

Uterine artery embolization vs hysterectomy in the treatment of symptomatic uterine fibroids: 10-year outcomes from the randomized EMMY trial

Annefleur M. de Bruijn, Willem M. Ankum, Jim A. Reekers et al. · American Journal of Obstetrics and Gynecology · 2016 · 388 citations · Full text

Medicine, Gynecology, Surgery +6