Computational Modeling and AI in Radiation Neuro-Oncology and Radiosurgery

Overview

Journal Adv Exp Med Biol

Specialties Biology
General Medicine

Date 2024 Nov 10

PMID 39523273

Authors

Cheng-Chia Lee

Huai-Che Yang

Hsiu-Mei Wu

Yen-Yu Lin

Chia-Feng Lu

Syu-Jyun Peng

Yu-Te Wu

Jason P Sheehan

Wan-Yuo Guo

Affiliations

Soon will be listed here.

Abstract

The chapter explores the extensive integration of artificial intelligence (AI) in healthcare systems, with a specific focus on its application in stereotactic radiosurgery. The rapid evolution of AI technology has led to promising developments in this field, particularly through the utilization of machine learning and deep learning models. The diverse implementation of AI algorithms was developed from various aspects of radiosurgery, including the successful detection of spontaneous tumors and the automated delineation or segmentation of lesions. These applications show potential for extension to longitudinal treatment follow-up. Additionally, the chapter highlights the established use of machine learning algorithms, particularly those incorporating radiomic-based analysis, in predicting treatment outcomes. The discussion encompasses current achievements, existing limitations, and the need for further investigation in the dynamic intersection of AI and radiosurgery.

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