Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics

<b>Introduction:</b> Accurate prediction of tumor dynamics following Gamma Knife radiosurgery (GKRS) is critical for optimizing treatment strategies for patients with brain metastases (BMs). Traditional machine learning (ML) algorithms have been widely used for this purpose; however, recent advancem...

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Bibliográfalaš dieđut

Váldodahkkit:	Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea, Cristian Constantin Volovăț
Materiálatiipa:	Artigo
Giella:	Inglês
Almmustuhtton:	MDPI AG 2024-09-01
Ráidu:	Diagnostics
Fáttát:	gamma knife radiosurgery (GKRS) brain metastasis tumor dynamics forecasting machine learning models autoencoders
Liŋkkat:	https://www.mdpi.com/2075-4418/14/18/2091
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