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Twitter Demographics
Mendeley readers
Chapter title |
Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation
|
---|---|
Chapter number | 29 |
Book title |
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
|
Published by |
Springer, Cham, October 2019
|
DOI | 10.1007/978-3-030-32245-8_29 |
Pubmed ID | |
Book ISBNs |
978-3-03-032244-1, 978-3-03-032245-8
|
Authors |
Junlin Yang, Nicha C. Dvornek, Fan Zhang, Julius Chapiro, MingDe Lin, James S. Duncan, Yang, Junlin, Dvornek, Nicha C., Zhang, Fan, Chapiro, Julius, Lin, MingDe, Duncan, James S. |
Twitter Demographics
The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 75% |
Netherlands | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 2 | 50% |
Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 149 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 149 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 41 | 28% |
Student > Master | 30 | 20% |
Researcher | 17 | 11% |
Student > Bachelor | 6 | 4% |
Student > Doctoral Student | 5 | 3% |
Other | 14 | 9% |
Unknown | 36 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 61 | 41% |
Engineering | 21 | 14% |
Mathematics | 3 | 2% |
Biochemistry, Genetics and Molecular Biology | 2 | 1% |
Medicine and Dentistry | 2 | 1% |
Other | 12 | 8% |
Unknown | 48 | 32% |