Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks.

By Daniel Kim, T. Mackinnon. 2017

447 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Health Informatics, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Maciej A. Mazurowski
2. Mustafa R. Bashir
3. Mateusz Buda
4. Ashirbani Saha

In Health Informatics

1. Maciej A. Mazurowski
2. Mustafa R. Bashir
3. Mateusz Buda
4. Ashirbani Saha

In Radiology, Nuclear Medicine and Imaging

1. Maciej A. Mazurowski
2. Mustafa R. Bashir
3. Mateusz Buda
4. Ashirbani Saha
5. Xin Zhu
6. Weihao Weng

Citations in the corpus

• Deep learning in radiology: an overview of the concepts and a survey of the state of the art with focus on MRI (2018, methodology): “In [43], the InceptionV3 network was fine-tuned and served as a feature extractor instead of previously used GoogLeNet.”
• A scoping review of transfer learning research on medical image analysis using ImageNet (2020, unknown): “, hip, knee, wrist) [39–41], suggesting the”