Cancer Prognosis by Using Machine Learning and Data Science: A Systematic Review-Reference-Cited by-同舟云学术

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Cancer Prognosis by Using Machine Learning and Data Science: A Systematic Review

Published:2023 Issue: Volume: Page:1-12
ISSN:2367-3370
Container-title:Proceedings of International Conference on Data Science and Applications
language:
Short-container-title:

Author:

Lakshmikanth Rajath Mohan T.,Jayapandian N.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-6631-6_1

Reference18 articles.

1. Bronkhorst AJ, Ungerer V, Holdenrieder S (2019) The emerging role of cell-free DNA as a molecular marker for cancer management. Biomol Detect Quantification 17:100087

2. Borgi M, Collacchi B, Ortona E, Cirulli F (2020) Stress and coping in women with breast cancer: unravelling the mechanisms to improve resilience. Neurosci Biobehav Rev 119:406–421

3. Yu C, Helwig EJ (2021) The role of AI technology in prediction, diagnosis and treatment of colorectal cancer. Artif Intell Rev 55(1):323–343

4. Sree SR, Vyshnavi SB, Jayapandian N (2019) Real-world application of machine learning and deep learning. In: 2019 International conference on smart systems and inventive technology (ICSSIT). IEEE, pp 1069–1073

5. Liao H, Xiong T, Peng J, Xu L, Liao M, Zhang Z, …, Zeng Y (2020) Classification and prognosis prediction from histopathological images of hepatocellular carcinoma by a fully automated pipeline based on machine learning. Ann Surg Oncol:1–11

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