The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review
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Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Deep Learning: Methods and Applications
Deng, L., & Yu, D. (2014) · Foundations and Trends® in Signal Processing · doi:10.1561/2000000039 · Cited by 3,480
Computer-aided diagnosis in medical imaging: historical review, current status and future potential
Doi, K. (2007) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2007.02.002 · Cited by 1,855
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
Artificial neural networks in medical diagnosis
Amato, F., López, A., Peña-Méndez, E. M., Vaňhara, P., Hampl, A., & Havel, J. (2013) · Journal of Applied Biomedicine · doi:10.2478/v10136-012-0031-x · Cited by 898
Giger, M. L., Chan, H., & Boone, J. (2008) · Medical Physics · doi:10.1118/1.3013555 · Cited by 311
Decision tree classifiers for automated medical diagnosis
Azar, A. T., & El-Metwally, S. M. (2013) · Neural Computing and Applications · doi:10.1007/s00521-012-1196-7 · Cited by 242
Deep learning based classification of breast tumors with shear-wave elastography
Zhang, Q., Xiao, Y., Dai, W., Suo, J., Wang, C., Shi, J., & Zheng, H. (2016) · Ultrasonics · doi:10.1016/j.ultras.2016.08.004 · Cited by 240
An automated confirmatory system for analysis of mammograms
Peng, W., Mayorga, R. V., & Hussein, E. M. A. (2016) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2015.09.019 · Cited by 43
Cited by
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
Murtaza, G., Shuib, L., Abdul Wahab, A. W., Mujtaba, G., Mujtaba, G., Nweke, H. F., Al-garadi, M. A., Zulfiqar, F., Raza, G., & Azmi, N. A. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09716-5 · Cited by 342
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
A comprehensive survey on federated learning techniques for healthcare informatics
Dasaradharami Reddy, K., & Gadekallu, T. R. (2023) · Computational Intelligence and Neuroscience · doi:10.1155/2023/8393990 · Cited by 126
Metadata
- Authors
- Yassin, N. I. R., Omran, S., El Houby, E. M. F., & Allam, H.
- Venue
- Computer Methods and Programs in Biomedicine
- Publisher
- Elsevier BV
- Published
- 2018-03
- Volume
- 156
- Pages
- 25-45
- ISSN
- 0169-2607 (ISSN-L)
- OpenAlex
- W2773642388
- Cited by
- 386
- References
- 9
- FWCI
- 6.46
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review. https://app.cochat.ai/papers/10.1016/j.cmpb.2017.12.012
- The paper
- Yassin, N. I. R., Omran, S., El Houby, E. M. F., & Allam, H. (2018). Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review. Computer Methods and Programs in Biomedicine. https://doi.org/10.1016/j.cmpb.2017.12.012
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.
