The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system
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Cites
You Only Look Once: Unified, Real-Time Object Detection
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ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380
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How transferable are features in deep neural networks?
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THE DIGITAL DATABASE FOR SCREENING MAMMOGRAPHY
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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
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Research works printed but not linked: 4
- Muramatsu, 2016, Breast mass classification on mammograms using radial local ternary patterns, Comput. Biol. Med., 72, 43, 10.1016/j.compbiomed.2016.03.007 · doi:10.1016/j.compbiomed.2016.03.007
- Li, 2017, Breast masses in mammography classification with local contour features, BioMed. Eng. OnLine, 16, 44, 10.1186/s12938-017-0332-0 · doi:10.1186/s12938-017-0332-0
- Al-antari, 2017, Hybrid model of computer-aided breast cancer diagnosis from digital mammograms, J. Scientific Eng., 04, 114
- M. Lin, Q. Chen and S. Yan, "Network in network," in arXiv:1312.4400, 2013. · arXiv
Cited by
YOLOv1 to v8: Unveiling Each Variant–A Comprehensive Review of YOLO
Hussain, M. (2024) · IEEE Access · doi:10.1109/access.2024.3378568 · Cited by 492
Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review
Houssein, E. H., Emam, M. M., Ali, A. A., & Suganthan, P. N. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114161 · Cited by 404
Sechopoulos, I., Teuwen, J., & Mann, R. (2021) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2020.06.002 · Cited by 341
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
Al-antari, M. A., Han, S.-M., & Kim, T.-S. (2020) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2020.105584 · Cited by 264
Self-citation
Metadata
- Authors
- Al-masni, M. A., Al-antari, M. A., Park, J.-M., Gi, G., Kim, T.-Y., Rivera, P., Valarezo, E., Choi, M.-T., Han, S.-M., & Kim, T.-S.
- Venue
- Computer Methods and Programs in Biomedicine
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 157
- Pages
- 85-94
- ISSN
- 0169-2607 (ISSN-L)
- OpenAlex
- W2793956967
- Cited by
- 482
- References
- 31
- FWCI
- 23.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Funders
- Ministry of Science, ICT & Future Planning (CISS- 2011–0031863)
- MOTIE (N0002252)
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- CoChat. (2026). Citation check: Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system. https://app.cochat.ai/papers/10.1016/j.cmpb.2018.01.017
- The paper
- Al-masni, M. A., Al-antari, M. A., Park, J.-M., Gi, G., Kim, T.-Y., Rivera, P., Valarezo, E., Choi, M.-T., Han, S.-M., & Kim, T.-S. (2018). Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system. Computer Methods and Programs in Biomedicine. https://doi.org/10.1016/j.cmpb.2018.01.017
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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.
