Cargando…
Deep learning methods for drug response prediction in cancer: Predominant and emerging trends
Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predictive models to study and treat cancer holds great promise in improving drug development and personalized design of trea...
Autores principales: | Partin, Alexander, Brettin, Thomas S., Zhu, Yitan, Narykov, Oleksandr, Clyde, Austin, Overbeek, Jamie, Stevens, Rick L. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975164/ https://www.ncbi.nlm.nih.gov/pubmed/36873878 http://dx.doi.org/10.3389/fmed.2023.1086097 |
Ejemplares similares
-
Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images
por: Partin, Alexander, et al.
Publicado: (2023) -
Learning curves for drug response prediction in cancer cell lines
por: Partin, Alexander, et al.
Publicado: (2021) -
Converting tabular data into images for deep learning with convolutional neural networks
por: Zhu, Yitan, et al.
Publicado: (2021) -
Publisher Correction: Converting tabular data into images for deep learning with convolutional neural networks
por: Zhu, Yitan, et al.
Publicado: (2021) -
Ensemble transfer learning for the prediction of anti-cancer drug response
por: Zhu, Yitan, et al.
Publicado: (2020)