Ovarian Cancer Proteome Analysis and Biomarker Discovery Using Machine Learning

This publication has 16 references indexed in Scilit:

• Bladder Cancer Microarray Analysis and Biomarker Discovery Using Machine Learning
  2023
• Lung Cancer Stages Classification Based on Differential Gene Expression
  2023
• Content-Based Image Retrieval Using Fused Convolutional Neural Networks
  2022
• COVID-19 X-rays Model Detection Using Convolution Neural Network
  2021
• Using machine learning to predict ovarian cancer
  International Journal of Medical Informatics, 2020
• LinkedOmics: analyzing multi-omics data within and across 32 cancer types
  Nucleic Acids Research, 2017
• Diagnostic accuracy of serum HE4, CA125 and ROMA in patients with ovarian cancer: a meta-analysis
  Tumor Biology, 2014
• Role of HE4, CA72.4, and CA125 in monitoring ovarian cancer
  Tumor Biology, 2012
• Comparison of a novel multiple marker assay vs the Risk of Malignancy Index for the prediction of epithelial ovarian cancer in patients with a pelvic mass
  American Journal of Obstetrics and Gynecology, 2010
• Support vector machines
  IEEE Intelligent Systems and their Applications, 1998