Aug 2026· Journal of Neuro-Oncology· Vol 179· 0 citations· 24 references
Medicine
TL;DR
An overview of the landscape of major U.S. neuro-oncology data resources is provided and how these datasets are used in contemporary research is evaluated, including population registries, clinical data networks, federal and consortium research cohorts, institutional datasets, specialized resources, and artificial intelligence benchmarking resources.
This narrative review aims to summarize the contribution of population-based cancer registries, hospital-based clinical registries, and administrative healthcare databases to the understanding and management of prostate, bladder, renal, and other genitourinary malignancies.
Ali Bourgi, Emmanuel Rusch, P. Bigot et al.· Current Urology Reports· 0 citations
Big data in cancer genomics offer substantial potential to advance precision oncology by enabling more accurate and personalized treatment strategies, however, overcoming technical, ethical, and infrastructural barriers is essential to ensure effective translation into clinical practice and equitable healthcare outcome...
Nur Vanu, Nur Mohammad, Fahad Ahmed et al.· Computational and Systems On...· 0 citations
This review synthesizes key developments in ML for oncology, covering foundational algorithms alongside emerging approaches, and describes future directions, including federated learning, graph neural networks, longitudinal modeling, and integration of real-world and wearable data to support precision oncology.
Kanishk Yadav, Taneesha Gupta· Journal of the Egyptian Nati...· 0 citations
Overall, AI research in neurodegenerative diseases suffers from significant limitations in reproducibility, data inclusivity, and clinical translatability, and a set of recommendations can be adopted to address these issues and improve reliability and downstream clinical utility.
W. Endrizzi, F. Ragni, S. Bovo et al.· Communications Medicine· 0 citations
The GENIE Data Model (GDM), a comprehensive, open-source, oncology data model for scalable, consistent, and interoperable data collection across solid tumors designed to effectively capture the patient's journey with cancer, is developed.
J. Hoppe, Jocelyn Lee, T. Akinyemiju et al.· Cancer Research Communicatio...· 0 citations
This review critically evaluates how advanced technologies operating in an integrated manner facilitate precision oncology by supporting fields such as genomics, transcriptomics, proteomics, metabolomics, and radiomics and provides an integrative roadmap for modern, multiomics-driven biomarker approaches in precision o...
Ujwal Havelikar, Atharva A. Shinde, Hrushikesh Mhaismale et al.· Omics· 0 citations
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