Your browser doesn't support javascript.
loading
Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier.
Geetha, R; Sivasubramanian, S; Kaliappan, M; Vimal, S; Annamalai, Suresh.
Affiliation
  • Geetha R; Bharath Institute of Higher Education and Research, Tamil Nadu, India.
  • Sivasubramanian S; Mohamed Sathak A J Engineering College, Chennai, India. drsivatbm2017@gmail.com.
  • Kaliappan M; Department of Computer Science and Engineering, Ramco Institute of Technology, Rajapalayam, India.
  • Vimal S; Department of Information Technology, National Engineering College, Kovilpatti, India.
  • Annamalai S; Department of CSE, Nehru Institute of Engineering and Technology, Coimbatore, India.
J Med Syst ; 43(9): 286, 2019 Jul 17.
Article in En | MEDLINE | ID: mdl-31312985
Subject(s)
Key words
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Uterine Cervical Neoplasms / Support Vector Machine Type of study: Clinical_trials / Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: J Med Syst Year: 2019 Document type: Article Affiliation country: India Country of publication: United States
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Uterine Cervical Neoplasms / Support Vector Machine Type of study: Clinical_trials / Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: J Med Syst Year: 2019 Document type: Article Affiliation country: India Country of publication: United States