Radiomics: the bridge between medical imaging and personalized medicine

P Lambin, RTH Leijenaar, TM Deist… - Nature reviews Clinical …, 2017 - nature.com
Radiomics, the high-throughput mining of quantitative image features from standard-of-care
medical imaging that enables data to be extracted and applied within clinical-decision …

Translation of AI into oncology clinical practice

I El Naqa, A Karolak, Y Luo, L Folio, AA Tarhini… - Oncogene, 2023 - nature.com
Artificial intelligence (AI) is a transformative technology that is capturing popular imagination
and can revolutionize biomedicine. AI and machine learning (ML) algorithms have the …

[HTML][HTML] Tracking tumor biology with radiomics: a systematic review utilizing a radiomics quality score

S Sanduleanu, HC Woodruff, EEC De Jong… - Radiotherapy and …, 2018 - Elsevier
Introduction: In this review we describe recent developments in the field of radiomics along
with current relevant literature linking it to tumor biology. We furthermore explore the …

[HTML][HTML] Distributed learning: develo** a predictive model based on data from multiple hospitals without data leaving the hospital–a real life proof of concept

A Jochems, TM Deist, J Van Soest, M Eble… - Radiotherapy and …, 2016 - Elsevier
Purpose One of the major hurdles in enabling personalized medicine is obtaining sufficient
patient data to feed into predictive models. Combining data originating from multiple …

Federated learning for multi-center imaging diagnostics: a simulation study in cardiovascular disease

A Linardos, K Kushibar, S Walsh, P Gkontra… - Scientific Reports, 2022 - nature.com
Deep learning models can enable accurate and efficient disease diagnosis, but have thus
far been hampered by the data scarcity present in the medical world. Automated diagnosis …

Decision support systems in oncology

S Walsh, EEC de Jong, JE van Timmeren… - JCO clinical cancer …, 2019 - ascopubs.org
Precision medicine is the future of health care: please watch the animation at https://vimeo.
com/241154708. As a technology-intensive and-dependent medical discipline, oncology will …

Development and validation of a radiomic signature to predict HPV (p16) status from standard CT imaging: a multicenter study

RTH Leijenaar, M Bogowicz, A Jochems… - The British journal of …, 2018 - academic.oup.com
Objectives: Human papillomavirus (HPV) positive oropharyngeal cancer (oropharyngeal
squamous cell carcinoma, OPSCC) is biologically and clinically different from HPV negative …

Magnetic resonance‐guided radiation therapy: a review

S Chin, CL Eccles, A McWilliam… - Journal of medical …, 2020 - Wiley Online Library
Magnetic resonance‐guided radiation therapy (MRgRT) is a promising approach to
improving clinical outcomes for patients treated with radiation therapy. The roles of image …

[HTML][HTML] Machine learning applications in radiation oncology

M Field, N Hardcastle, M Jameson, N Aherne… - Physics and Imaging in …, 2021 - Elsevier
Abstract Machine learning technology has a growing impact on radiation oncology with an
increasing presence in research and industry. The prevalence of diverse data including 3D …

[HTML][HTML] Develo** and validating a survival prediction model for NSCLC patients through distributed learning across 3 countries

A Jochems, TM Deist, I El Naqa, M Kessler… - International Journal of …, 2017 - Elsevier
Purpose Tools for survival prediction for non-small cell lung cancer (NSCLC) patients
treated with chemoradiation or radiation therapy are of limited quality. In this work, we …