Skip to content
Log in
Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

D. Golubev

View on Semantic Scholar

3 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Review Open access Oct 2026

Artificial intelligence in cancer transcriptomics: methods, applications in oncology, and limitations

Background. Transcriptomic data show which genes are active in cells and tissues. Machine-learning and deep-learning methods use these data to classify samples, integrate different datasets, and predict biological properties and treatment response. In oncology, a major challenge is transferring patterns identified i...

I. A. Solovev, D. Golubev · 0 citations
Review Open access Oct 2026

Machine learning for predicting and overcoming tumor radioresistance: current approaches

Introduction . Intertumoral differences in biological response to radiation remain a major obstacle to the full personalization of radiotherapy. Radioresistance is driven by multiple factors, including DNA repair, hypoxia, metabolic reprogramming, and cancer stem cells, which renders the search for a single biomarke...

I. A. Soloviev, D. Golubev · 0 citations
#federated learning Review Open access Sep 2026

Oncology databases for predicting tumor radiosensitivity and chemosensitivity: a critical translational synthesis

A critical translational synthesis of oncology databases and computational resources used to predict tumor radiosensitivity and chemosensitivity and shows homologous recombination deficiency in the context of DNA-damaging therapy and genomic-adjusted radiation dose as a research predictor of radiotherapy benefit is dem...

I. A. Solovev, D. Golubev · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.