ICMFKC with optimize XGBoost classification for breast cancer image screening and detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-18029-3.pdf
Reference61 articles.
1. Lahoura V, Singh H, Aggarwal A, Sharma B, Mohammed MA, Damaševičius R, Kadry S, Cengiz K et al (2021) Cloud computing-based framework for breast cancer diagnosis using extreme learning machine. Diagnostics 11(2):241
2. Pezeshki H (2022) Breast tumor segmentation in digital mammograms using spiculated regions. Biomed Signal Process Control 76:103652
3. Singh H, Sharma V, Singh D (2022) Comparative analysis of proficiencies of various textures and geometric features in breast mass classification using k-nearest neighbor. Vis Comput Ind Biomed Art 5:1–19
4. Raghavendra U, Gudigar A, Ciaccio EJ, Ng KH, Chan WY, Rahmat K, Acharya UR (2021) 2DSM vs FFDM: A computer aided diagnosis based comparative study for the early detection of breast cancer. Expert Syst 38:e12474
5. Almalki YE, Soomro TA, Irfan M, Alduraibi SK, Ali A (1868) Impact of image enhancement module for analysis of mammogram images for diagnostics of breast cancer. Sensors 22:1868
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