Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Komunikasi Fisika Indonesia
Luqyana Adha Azwat
Department of Physics, University of Indonesia, Depok, Indonesia
Earth & Planetary Sciences Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Physics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Random forest algorithm for precision dose prediction in brain cancer radiotherapy Luqyana Adha Azwat; Prawito Prajitno; Dwi Seno Kuncoro Sihono; Dewa Ngurah Yudhi Persada
Indonesian Physics Communication Vol 21, No 2 (2024)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.21.2.183-186

Abstract

Improving dose optimization during clinical planning using the treatment planning system for radiotherapy patients is crucial, yet executing this process can be time-consuming and reliant on the expertise of medical physicists. This research focuses on dose prediction employing machine learning for the planning target volume (PTV) and organ at risk (OAR) in cases of brain cancer treated with the volumetric modulated arc therapy planning technique. Utilizing DICOM planning data from brain cancer cases, this study utilizes extracted radiomic and dosiomic values as inputs and outputs for the research, employing a random forest algorithm model. Evaluation of the model reveals its effectiveness in predicting doses for PTV in brain cancer and OAR, with predicted homogeneity index and conformity index values of 0.14 ± 0.04 and 0.95 ± 0.01, respectively, compared to clinical values of 0.14 ± 0.13 and 0.94 ± 0.13. Thus, the random forest model demonstrates proficiency in predicting doses for brain cancer PTV and OAR, with an mean square error value of 0.017.
Co-Authors Dewa Ngurah Yudhi Persada Dwi Seno Kuncoro Sihono Prawito Prajitno