The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Large scale deep learning for computer aided detection of mammographic lesions
Kooi, T., Litjens, G., van Ginneken, B., Gubern-Mérida, A., Sánchez, C. I., Mann, R., den Heeten, A., & Karssemeijer, N. (2017) · Medical Image Analysis · doi:10.1016/j.media.2016.07.007 · Cited by 965
Cited by
Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening
Wu, N., Phang, J., Park, J., Shen, Y., Huang, Z., Zorin, M., Jastrzebski, S., Fevry, T., Katsnelson, J., Kim, E., et al. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2945514 · Cited by 689
Breast cancer detection using deep convolutional neural networks and support vector machines
Ragab, D. A., Sharkas, M., Marshall, S., & Ren, J. (2019) · PeerJ · doi:10.7717/peerj.6201 · Cited by 513
Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis
Wang, X., Chen, H., Gan, C., Lin, H., Dou, Q., Tsougenis, E., Huang, Q., Cai, M., & Heng, P.-A. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2935141 · Cited by 408
Thoracic Disease Identification and Localization with Limited Supervision
Li, Z., Wang, C., Han, M., Xue, Y., Wei, W., Li, L.-J., & Fei-Fei, L. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00865 · Cited by 313
Deep convolutional neural networks for mammography: advances, challenges and applications
Abdelhafiz, D., Yang, C., Ammar, R., & Nabavi, S. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2823-4 · Cited by 274
Metadata
- Authors
- Zhu, W., Lou, Q., Vang, Y. S., & Xie, X.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2017
- Pages
- 603-611
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2964275459
- Cited by
- 214
- References
- 2
- FWCI
- 13.97
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification. https://app.cochat.ai/papers/10.1007/978-3-319-66179-7_69
- The paper
- Zhu, W., Lou, Q., Vang, Y. S., & Xie, X. (2017). Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-66179-7_69
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.