Machine learning-based models for prediction of toxicity outcomes in radiotherapy

LJ Isaksson, M Pepa, M Zaffaroni, G Marvaso… - Frontiers in …, 2020 - frontiersin.org
In order to limit radiotherapy (RT)-related side effects, effective toxicity prediction and
assessment schemes are essential. In recent years, the growing interest toward artificial …

A survey on computational intelligence approaches for predictive modeling in prostate cancer

G Cosma, D Brown, M Archer, M Khan… - Expert systems with …, 2017 - Elsevier
Predictive modeling in medicine involves the development of computational models which
are capable of analysing large amounts of data in order to predict healthcare outcomes for …

A machine-learning-based prediction method for hypertension outcomes based on medical data

W Chang, Y Liu, Y Xiao, X Yuan, X Xu, S Zhang… - Diagnostics, 2019 - mdpi.com
The outcomes of hypertension refer to the death or serious complications (such as
myocardial infarction or stroke) that may occur in patients with hypertension. The outcomes …

Design and selection of machine learning methods using radiomics and dosiomics for normal tissue complication probability modeling of xerostomia

HS Gabryś, F Buettner, F Sterzing, H Hauswald… - Frontiers in …, 2018 - frontiersin.org
Purpose The purpose of this study is to investigate whether machine learning with dosiomic,
radiomic, and demographic features allows for xerostomia risk assessment more precise …

Autoencoder based feature selection method for classification of anticancer drug response

X Xu, H Gu, Y Wang, J Wang, P Qin - Frontiers in genetics, 2019 - frontiersin.org
Anticancer drug responses can be varied for individual patients. This difference is mainly
caused by genetic reasons, like mutations and RNA expression. Thus, these genetic …

Predicting toxicity in radiotherapy for prostate cancer

V Landoni, C Fiorino, C Cozzarini, G Sanguineti… - Physica Medica, 2016 - Elsevier
This comprehensive review addresses most organs at risk involved in planning optimization
for prostate cancer. It can be considered an update of a previous educational review that …

Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression

M Ammad-Ud-Din, SA Khan, K Wennerberg… - …, 2017 - academic.oup.com
Motivation A prime challenge in precision cancer medicine is to identify genomic and
molecular features that are predictive of drug treatment responses in cancer cells. Although …

Dosiomics-based prediction of radiation-induced hypothyroidism in nasopharyngeal carcinoma patients

W Ren, B Liang, C Sun, R Wu, K Men, Y Xu, F Han, J Yi… - Physica Medica, 2021 - Elsevier
Purpose To predict the incidence of radiation-induced hypothyroidism (RHT) in
nasopharyngeal carcinoma (NPC) patients, dosiomics features based prediction models …

Machine learning for radiation outcome modeling and prediction

Y Luo, S Chen, G Valdes - Medical physics, 2020 - Wiley Online Library
Aims This review paper intends to summarize the application of machine learning to
radiotherapy outcome modeling based on structured and un‐structured radiation oncology …

A systematic post-QUANTEC review of tolerance doses for late toxicity after prostate cancer radiation therapy

CE Olsson, A Jackson, JO Deasy, M Thor - International Journal of …, 2018 - Elsevier
Purpose The aims of this study were to systematically review tolerance doses for late distinct
gastrointestinal (GI), genitourinary (GU), and sexual dysfunction (SD) symptoms after …