Classification of Cancer Model for Clinically Actionable Genetic Mutations Using Machine Learning

Authors

  • Anandh B.1, Akash U.1, Subhashini R.2, Sethuraman R.2, Saravanan M.2

DOI:

https://doi.org/10.37506/mlu.v20i4.1763

Keywords:

Genetic Mutations, Clinical Evidences, Clinical Pathologist, Natural Language Process.

Abstract

Classification of Cancer Model Clinically Actionable Genetic Mutations Using Machine Learning
Algorithms. Its task is to classify genes based on text evidence from clinical issues with good results. If a
normal person has symptoms of cancer we can find it easily, but we have nine types of viruses in cancer
in that which type of viruses has been attacked to the person cannot be easily predict by the doctors. So in
hospitals there will be a clinical pathologist. Clinical pathologist has the data’s of cancer attacked before and
he will collect the gene sample and the person blood sample and predict which type of virus of cancer will
attack to the person.

Author Biography

  • Anandh B.1, Akash U.1, Subhashini R.2, Sethuraman R.2, Saravanan M.2

    1Student, Department of Information Technology, Sathyabama Institute of Science and Technology,
    Chennai-600119, India, 2Faculty, School of Computing , Sathyabama Institute of Science and Technology,
    Chennai-600119, India

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Published

2020-11-18

Issue

Vol. 20 No. 4 (2020): Medico-Legal Update

Section

Articles

How to Cite

Classification of Cancer Model for Clinically Actionable Genetic Mutations Using Machine Learning. (2020). Medico Legal Update, 20(4), 51-55. https://doi.org/10.37506/mlu.v20i4.1763