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Deep learning in cancer diagnosis, prognosis and treatment selection - PMC
Source: ncbi.nlm.nih.gov
Article summary:
1. Deep learning is a powerful tool for cancer diagnosis, prognosis and treatment selection.
2. This article reviews the applications of deep learning in genomics, radiation oncology, digital pathology and other areas related to cancer diagnosis and treatment.
3. The article also discusses the potential of deep learning to improve risk stratification and provide patient-specific molecular subnetworks for metastasis prediction in breast cancer.
Article analysis:
The article provides an overview of the applications of deep learning in cancer diagnosis, prognosis and treatment selection. It is well-researched and provides a comprehensive review of the current state of research in this field. The authors have included a wide range of sources from both academic journals and online sources, which adds to the trustworthiness of the article.
The article does not appear to be biased or one-sided as it presents both sides equally by providing evidence for both positive and negative aspects of deep learning in cancer diagnosis, prognosis and treatment selection. Furthermore, it does not contain any promotional content or partiality towards any particular technology or approach.
The article does not appear to be missing any points of consideration or evidence for its claims made as it provides detailed information about each application discussed in the article with relevant citations from reliable sources. Additionally, all possible risks associated with using deep learning are noted throughout the article.
In conclusion, this article is trustworthy and reliable as it provides an unbiased overview of deep learning applications in cancer diagnosis, prognosis and treatment selection with evidence from reliable sources.