Work

Mathematical Modelling of Survival in Low Grade Gliomas at Malignant Transformation with XGBoost.

Year: 2024

Type: conference-paper

Study design: Observational Study

Source: Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition

DOI: 10.58530/2024/3775

Authors: Lily Tan, James Ruffle, Rees Jeremy, Michael Kosmin, Parashkev Nachev, Harpreet Hyare

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4404745918

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