AI-Driven Radiotherapy Solutions for Rare and Complex Cancers Using Multi-Omics Approaches
Authors: Nitiraj V. Kulkarni et al.
Year:
Venue: Springer Book Chapter — Pages 409–419
Publisher: Springer
Type: book-chapter (published)
Abstract
Explores AI-driven radiotherapy solutions for rare and complex cancers using multi-omics data integration approaches.
This work intersects with research areas including AI, radiotherapy, rare cancers, multi-omics, oncology, precision medicine, cancer treatment, and machine learning. It is part of the broader research portfolio of Nitiraj V. Kulkarni in the domain of peer-reviewed academic publishing.
Keywords & Topics
AI, radiotherapy, rare cancers, multi-omics, oncology, precision medicine, cancer treatment, machine learning
How to Cite
APA
Nitiraj V. Kulkarni et al. (2025). AI-Driven Radiotherapy Solutions for Rare and Complex Cancers Using Multi-Omics Approaches. Springer Book Chapter, Pages 409–419. Springer.
IEEE
Nitiraj V. Kulkarni et al., "AI-Driven Radiotherapy Solutions for Rare and Complex Cancers Using Multi-Omics Approaches," Springer Book Chapter, Pages 409–419, 2025.
BibTeX
@article{2025_ai_radiotherapy_rare_cancers_multi_omics,
title={AI-Driven Radiotherapy Solutions for Rare and Complex Cancers Using Multi-Omics Approaches},
author={Nitiraj V. Kulkarni et al.},
journal={Springer Book Chapter},
year={2025},
publisher={Springer}
}Identifiers & Links
Publisher link: https://link.springer.com
Last updated: 2025-01-01
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About the Author
Nitiraj V. Kulkarni is an AI safety and cybersecurity researcher based in Pune, India, with 35+ peer-reviewed publications, 5 patents, 6 copyright registrations, and 15,000+ open datasets published on Kaggle and Zenodo. He serves as a peer reviewer for 11+ international journals and conferences. Read full profile.