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Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Nature medicine, 2022-05, Vol.28 (5), p.924-933

2022

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Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

BMJ (Online), 2022-05, Vol.377, p.e070904

2022

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Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Nature medicine, 2022-10, Vol.28 (10), p.2218-2218

2022

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Big data and machine learning in radiation oncology: state of the art and future prospects

Cancer letters, 2016-11, Vol.382 (1), p.110-117

2016

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SP-1001 2030: The end of the "one-dose fits all" concept?

Radiotherapy and oncology, 2023-05, Vol.182, p.S837-S838

. Bibault, J.

2023

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SP-1027 The Matrix: Treatment decisions and optimal steering of radiotherapy will be based on big data cloudcomputing

Radiotherapy and oncology, 2022-05, Vol.170, p.S865-S865

Bibault, J.

2022

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A Comparative Study of Large Language Models for Generating Summaries of Breast Cancer Patient-Reported Treatment Toxicities

International journal of radiation oncology, biology, physics, 2024-10, Vol.120 (2), p.e666-e666

2024

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Deep Learning and Radiomics predict complete response after neo-adjuvant chemoradiation for locally advanced rectal cancer

Scientific reports, 2018-08, Vol.8 (1), p.12611-8, Article 12611

2018

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When Chatbots Meet Patients: One-Year Prospective Study of Conversations Between Patients With Breast Cancer and a Chatbot

JMIR cancer, 2019-05, Vol.5 (1), p.e12856

2019

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Salvage stereotactic reirradiation for intraprostatic cancer recurrence: A large retrospective study

The Prostate, 2023-06, Vol.83 (8), p.743-750

2023

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Development and validation of a model to predict survival in colorectal cancer using a gradient-boosted machine

Gut, 2021-05, Vol.70 (5), p.884-889

2021

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Radiomics: A primer for the radiation oncologist

Cancer radiothérapie, 2020-08, Vol.24 (5), p.403-410

2020

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SP-0009 Clinical applications of AI for Radiation Oncology

Radiotherapy and oncology, 2019-04, Vol.133, p.S4-S4

Bibault, J.

2019

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Deep Learning: A Review for the Radiation Oncologist

Frontiers in oncology, 2019-10, Vol.9, p.977-977

2019

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Deep learning for automated segmentation in radiotherapy: a narrative review

British journal of radiology, 2024-01, Vol.97 (1153), p.13-20

2024

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SP-0317: What is the Young ESTRO Committee and what can it do for young radiation oncology professionnals?

Radiotherapy and oncology, 2016-04, Vol.119, p.S146-S147

Bibault, J.E

2016

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Predicting Survival in Prostate Cancer Patients with Interpretable Artificial Intelligence

International journal of radiation oncology, biology, physics, 2020-11, Vol.108 (3), p.S117-S118

2020

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Automated contour propagation of the prostate from pCT to CBCT images via deep unsupervised learning

Medical physics (Lancaster), 2021-04, Vol.48 (4), p.1764-1770

2021

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A Chatbot Versus Physicians to Provide Information for Patients With Breast Cancer: Blind, Randomized Controlled Noninferiority Trial

Journal of medical Internet research, 2019-11, Vol.21 (11), p.e15787

2019

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Stereotactic body radiation therapy for hepatocellular carcinoma: prognostic factors of local control, overall survival, and toxicity

PloS one, 2013-10, Vol.8 (10), p.e77472

2013

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Pilot applications of GPT-4 in radiation oncology: Summarizing patient symptom intake and targeted chatbot applications

Radiotherapy and oncology, 2024-01, Vol.190, p.109978, Article 109978

2024

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Radiomics and Machine Learning for Radiotherapy in Head and Neck Cancers

Frontiers in oncology, 2019-03, Vol.9, p.174-174

2019

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Labeling for Big Data in radiation oncology: The Radiation Oncology Structures ontology

PloS one, 2018-01, Vol.13 (1), p.e0191263-e0191263

2018

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Ethical Aspects of Artificial Intelligence in Radiation Oncology

Seminars in radiation oncology, 2022-10, Vol.32 (4), p.442-448

2022

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Assessment of bias in scoring of AI-based radiotherapy segmentation and planning studies using modified TRIPOD and PROBAST guidelines as an example

Radiotherapy and oncology, 2024-05, Vol.194, p.110196, Article 110196

2024

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Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Big data and machine learning in radiation oncology: state of the art and future prospects

SP-1001 2030: The end of the "one-dose fits all" concept?

SP-1027 The Matrix: Treatment decisions and optimal steering of radiotherapy will be based on big data cloudcomputing

A Comparative Study of Large Language Models for Generating Summaries of Breast Cancer Patient-Reported Treatment Toxicities

Deep Learning and Radiomics predict complete response after neo-adjuvant chemoradiation for locally advanced rectal cancer

When Chatbots Meet Patients: One-Year Prospective Study of Conversations Between Patients With Breast Cancer and a Chatbot

Salvage stereotactic reirradiation for intraprostatic cancer recurrence: A large retrospective study

Development and validation of a model to predict survival in colorectal cancer using a gradient-boosted machine

Radiomics: A primer for the radiation oncologist

SP-0009 Clinical applications of AI for Radiation Oncology

Deep Learning: A Review for the Radiation Oncologist

Deep learning for automated segmentation in radiotherapy: a narrative review

SP-0317: What is the Young ESTRO Committee and what can it do for young radiation oncology professionnals?

Predicting Survival in Prostate Cancer Patients with Interpretable Artificial Intelligence

Automated contour propagation of the prostate from pCT to CBCT images via deep unsupervised learning

A Chatbot Versus Physicians to Provide Information for Patients With Breast Cancer: Blind, Randomized Controlled Noninferiority Trial

Stereotactic body radiation therapy for hepatocellular carcinoma: prognostic factors of local control, overall survival, and toxicity

Pilot applications of GPT-4 in radiation oncology: Summarizing patient symptom intake and targeted chatbot applications

Radiomics and Machine Learning for Radiotherapy in Head and Neck Cancers

Labeling for Big Data in radiation oncology: The Radiation Oncology Structures ontology

Ethical Aspects of Artificial Intelligence in Radiation Oncology

Assessment of bias in scoring of AI-based radiotherapy segmentation and planning studies using modified TRIPOD and PROBAST guidelines as an example

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