Radiation therapy response prediction for head and neck cancer using multimodal imaging and multiview dynamic graph autoencoder feature selection

The results demonstrated that the proposed predictive model is able to predict H&N cancer treatment response. MVFS provided better interpretabilityfor analysing features and preserved the inter-correlation among features from different imaging modalities.

Authors

Aryan Safakish
Lakshmanan Sannachi (ORCID: https://orcid.org/0000-0002-9775-0224)
Laurentius O. Osapoetra (ORCID: https://orcid.org/0000-0001-9278-0953)
David Alberico
Amir Moslemi (ORCID: https://orcid.org/0000-0003-0849-1943)
Gregory J. Czarnota (ORCID: https://orcid.org/0000-0002-9973-4586)

Institutions

Sunnybrook Health Science Centre (CA)
University of Toronto (CA)
Health Sciences Centre (CA)
Sunnybrook Research Institute
Toronto Metropolitan University (CA)

Publication Details

Journal: Medical Physics
Published: 2025-09-22
DOI: https://doi.org/10.1002/mp.70026
Citations: 2
Primary Topic: Radiomics and Machine Learning in Medical Imaging
Type: article
Field-Weighted Citation Impact: 2.72

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article

Radiation therapy response prediction for head and neck cancer using multimodal imaging and multiview dynamic graph autoencoder feature selection

Aryan Safakish, Lakshmanan Sannachi, Laurentius O. Osapoetra, David Alberico et al.

Sep 22, 2025

2 citations

Medical Physics

Radiomics and Machine Learning in Medical Imaging

2.72

article

Radiation therapy response prediction for head and neck cancer using multimodal imaging and multiview dynamic graph autoencoder feature selection

Aryan Safakish, Lakshmanan Sannachi, Laurentius O. Osapoetra, David Alberico, Amir Moslemi, Gregory J. Czarnota

September 22, 2025article en

2 citations

Abstract

The results demonstrated that the proposed predictive model is able to predict H&N cancer treatment response. MVFS provided better interpretabilityfor analysing features and preserved the inter-correlation among features from different imaging modalities.

Medical PhysicsVol. 52(10)

Sunnybrook Health Science Centre (CA), University of Toronto (CA), Health Sciences Centre (CA), Sunnybrook Research Institute, Toronto Metropolitan University (CA)

Openalex Percentile: Top 9%

Radiomics and Machine Learning in Medical Imaging

2.72

DOI Open Access PDF OpenAlex

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Radiation therapy response prediction for head and neck cancer using multimodal imaging and multiview dynamic graph autoencoder feature selection — Aryan Safakish, Lakshmanan Sannachi, et al. · Medical Physics (2025) | TGRS Research Map | TGRS