Genomic and Transcriptomic Predictors of Response to Immune Checkpoint Inhibitors in Melanoma Patients: A Machine Learning Approach

SIMPLE SUMMARY: Our work provides novel transcriptomic biomarkers that can accurately predict immune checkpoint inhibitors (ICIs) response in melanoma patients. Using a bioinformatics analysis and supervised machine learning approach, we developed four random-forest classifiers based on clinical, ge...

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Detalles Bibliográficos
Autores principales: Ahmed, Yaman B., Al-Bzour, Ayah N., Ababneh, Obada E., Abushukair, Hassan M., Saeed, Anwaar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688789/
https://www.ncbi.nlm.nih.gov/pubmed/36428698
http://dx.doi.org/10.3390/cancers14225605

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688789/
https://www.ncbi.nlm.nih.gov/pubmed/36428698
http://dx.doi.org/10.3390/cancers14225605

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