Literature DB >> 30191856

The Future of Artificial Intelligence in Radiation Oncology.

Reid F Thompson1, Gilmer Valdes2, Clifton David Fuller3, Colin M Carpenter4, Olivier Morin2, Sanjay Aneja5, William D Lindsay6, Hugo J W L Aerts7, Barbara Agrimson8, Curtiland Deville9, Seth A Rosenthal10, James B Yu5, Charles R Thomas8.   

Abstract

Mesh：

Year:  2018        PMID： 30191856     DOI： 10.1016/j.ijrobp.2018.05.072

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN： 0360-3016            Impact factor:   7.038


× No keyword cloud information.
  4 in total

1.  Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.

Authors:  Jue Jiang; Yu-Chi Hu; Neelam Tyagi; Pengpeng Zhang; Andreas Rimner; Joseph O Deasy; Harini Veeraraghavan
Journal:  Med Phys       Date:  2019-08-20       Impact factor: 4.071

Review 2.  Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives.

Authors:  Bruno Fionda; Luca Boldrini; Andrea D'Aviero; Valentina Lancellotta; Maria Antonietta Gambacorta; György Kovács; Stefano Patarnello; Vincenzo Valentini; Luca Tagliaferri
Journal:  J Contemp Brachytherapy       Date:  2020-10-30

3.  100% peer review in radiation oncology: is it feasible?

Authors:  E Martin-Garcia; F Celada-Álvarez; M J Pérez-Calatayud; M Rodriguez-Pla; O Prato-Carreño; D Farga-Albiol; O Pons-Llanas; S Roldán-Ortega; E Collado-Ballesteros; F J Martinez-Arcelus; Y Bernisz-Diaz; V A Macias; J Chimeno; J Gimeno-Olmos; F Lliso; V Carmona; J C Ruiz; J Pérez-Calatayud; A Tormo-Micó; A J Conde-Moreno
Journal:  Clin Transl Oncol       Date:  2020-06-15       Impact factor: 3.405

4.  Barriers and facilitators to the adoption of artificial intelligence in radiation oncology: A New Zealand study.

Authors:  Koki Victor Mugabe
Journal:  Tech Innov Patient Support Radiat Oncol       Date:  2021-04-21
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.