Prognosis of Cervical Cancer Disease by Applying Machine Learning Techniques

Article Properties
  • Language
    English
  • DOI (url)
    10.1142/s0218126623500196
  • Publication Date
    2022/08/10
  • Journal
    Journal of Circuits, Systems and Computers
  • Indian UGC (Journal)
  • Refrences
    35
  • Citations
    16
  • Gaurav Kumawat Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur 302034, Rajasthan, India
  • Santosh Kumar Vishwakarma Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur 302034, Rajasthan, India
  • Prasun Chakrabarti ITM SLS Baroda University, Vadodara 391510, Gujarat, India
  • Pankaj Chittora Department of Computer Science and Engineering, Manipal University Jaipur, Rajasthan, India
  • Tulika Chakrabarti Department of Basic Science, Sir Padampat Singhania University, Udaipur-313601, Rajasthan, India
  • Jerry Chun-Wei Lin Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5063, Bergen, Norway ORCID (unauthenticated)
Abstract
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Cite
Kumawat, Gaurav, et al. “Prognosis of Cervical Cancer Disease by Applying Machine Learning Techniques”. Journal of Circuits, Systems and Computers, vol. 32, no. 01, 2022, https://doi.org/10.1142/s0218126623500196.
Kumawat, G., Vishwakarma, S. K., Chakrabarti, P., Chittora, P., Chakrabarti, T., & Lin, J. C.-W. (2022). Prognosis of Cervical Cancer Disease by Applying Machine Learning Techniques. Journal of Circuits, Systems and Computers, 32(01). https://doi.org/10.1142/s0218126623500196
Kumawat G, Vishwakarma SK, Chakrabarti P, Chittora P, Chakrabarti T, Lin JCW. Prognosis of Cervical Cancer Disease by Applying Machine Learning Techniques. Journal of Circuits, Systems and Computers. 2022;32(01).
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Refrences
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Refrences Analysis
Category Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science7
Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens4
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware2
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks2
Technology: Mechanical engineering and machinery2
The category Science: Mathematics: Instruments and machines: Electronic computers. Computer science 7 is the most frequently represented among the references in this article. It primarily includes studies from Frontiers in Oncology and Clinical Microbiology Reviews. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
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Citations Analysis
The first research to cite this article was titled A Review on Spectroscopy and its Classification and was published in 2022. The most recent citation comes from a 2023 study titled A Review on Spectroscopy and its Classification . This article reached its peak citation in 2022 , with 15 citations.It has been cited in 4 different journals. Among related journals, the 4 cited this research the most, with 5 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year