Analysis on Machine Learning Strategies for Carcinoma Detection Biomarker

Author:

Verma Shairal1ORCID,Verma Prem Kumari2ORCID,Singh Nagendra Pratap3ORCID

Affiliation:

1. Department of Computer Science and Engineering, Dr. B R Ambedkar National Institute of Technology, India

2. CSE, NIT, Jalandhar, India

3. Computer science and engineering, NIT Jalandhar, India

Publisher

ACM

Reference42 articles.

1. Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Hasan Gharaibeh, and Sujeet Shrestha. 2023. Classification Of Cancer Genome Atlas Glioblastoma Multiform (TCGA-GBM) Using Machine Learning Method. In 2023 IEEE International Conference on Electro Information Technology (eIT). IEEE, 265–270.

2. Abedalrhman Alkhateeb, Iman Rezaeian, Siva Singireddy, Dora Cavallo-Medved, Lisa A Porter, and Luis Rueda. 2019. Transcriptomics signature from next-generation sequencing data reveals new transcriptomic biomarkers related to prostate cancer. Cancer informatics 18 (2019), 1176935119835522.

3. The FDA NIH Biomarkers, EndpointS, and other Tools (BEST) resource in neuro-oncology

4. Machine learning and the physical sciences

5. A survey on feature selection methods

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