Classification of clinically actionable genetic mutations in cancer patients using machine learning-based precision diagnostics-Reference-Cited by-同舟云学术

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Classification of clinically actionable genetic mutations in cancer patients using machine learning-based precision diagnostics

Published:2023 Issue: Volume: Page:395-412
ISSN:
Container-title:Nanotechnology Principles in Drug Targeting and Diagnosis
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Author:

Thakare Anuradha,Chaudhari Shruti,Baradkar Hemant

Publisher

Elsevier

Reference36 articles.

1. Adriana, M.E., Mesnita, G., 2019. Light GBM machine learning algorithm to online click fraud detection, J. Inf. Assur. Cybersecurity, 2019, 12, Available from: https://doi.org/10.5171/2019.263928.

2. Novel risk genes for systemic lupus erythematosus predicted by random forest classification;Almlof;Sci. Rep.,2017

3. Classification of genetic mutations for cancer treatment with machine learning approaches;Bei;Int. J. Desig. Anal. Tools Integr. Circuits Syst.,2018

4. Application of logistic regression in natural language processing;Bhartendoo;Int. J. Eng. Res. Technol.,2020

5. Challenges of identifying clinically actionable genetic variants for precision medicine;Carter;J. Healthc. Eng.,2016

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