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

Autor:	R Subhashini, M Saravanan, U Akash, B Anandh, R Sethuraman
Rok vydání:	2020
Předmět:	business.industry Sample (material) Cancer Model medicine Cancer Bioinformatics medicine.disease business Pathology and Forensic Medicine Task (project management)
Zdroj:	Medico-Legal Update. 20
ISSN:	0974-1283 0971-720X
DOI:	10.37506/mlu.v20i4.1763
Popis:	Classification of Cancer Model Clinically Actionable Genetic Mutations Using Machine LearningAlgorithms. Its task is to classify genes based on text evidence from clinical issues with good results. If anormal person has symptoms of cancer we can find it easily, but we have nine types of viruses in cancerin that which type of viruses has been attacked to the person cannot be easily predict by the doctors. So inhospitals there will be a clinical pathologist. Clinical pathologist has the data’s of cancer attacked before andhe will collect the gene sample and the person blood sample and predict which type of virus of cancer willattack to the person.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ae8bf5e5a8fe4198b7e2aa090950313d https://doi.org/10.37506/mlu.v20i4.1763 Zobrazit plný text záznamu