AIMC Topic: Radiation Oncology

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Understanding machine learning classifier decisions in automated radiotherapy quality assurance.

Physics in medicine and biology Jan 17, 2022
The complexity of generating radiotherapy treatments demands a rigorous quality assurance (QA) process to ensure patient safety and to avoid clinically significant errors. Machine learning classifiers have been explored to augment the scope and effic...
Research Design Male Radiation Oncology Humans Machine Learning
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A Glimmer of Hope Within the Mountain of Hype - Reviewing the Role of Artificial Intelligence in Radiotherapy.

Clinical oncology (Royal College of Radiologists (Great Britain)) Dec 16, 2021
Radiation Oncology Humans Artificial Intelligence
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Deep Learning for Radiotherapy Outcome Prediction Using Dose Data - A Review.

Clinical oncology (Royal College of Radiologists (Great Britain)) Dec 16, 2021
Artificial intelligence, and in particular deep learning using convolutional neural networks, has been used extensively for image classification and segmentation, including on medical images for diagnosis and prognosis prediction. Use in radiotherapy...
Deep Learning Radiation Oncology Radiotherapy Dosage Artificial Intelligence Prognosis Humans
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Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.

International journal of molecular sciences Dec 10, 2021
Computational approaches including machine learning, deep learning, and artificial intelligence are growing in importance in all medical specialties as large data repositories are increasingly being optimised. Radiation oncology as a discipline is at...
Humans Machine Learning Glioma Central Nervous System Neoplasms Radiation Oncology Biomarkers, Tumor Computational Biology
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Application of deep learning to auto-delineation of target volumes and organs at risk in radiotherapy.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique Oct 26, 2021
The technological advancement heralded the arrival of precision radiotherapy (RT), thereby increasing the therapeutic ratio and decreasing the side effects from treatment. Contour of target volumes (TV) and organs at risk (OARs) in RT is a complicate...
Radiotherapy Planning, Computer-Assisted Observer Variation Humans Radiation Oncology Organs at Risk Deep Learning
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Natural language processing and machine learning to assist radiation oncology incident learning.

Journal of applied clinical medical physics Oct 5, 2021
PURPOSE: To develop a Natural Language Processing (NLP) and Machine Learning (ML) pipeline that can be integrated into an Incident Learning System (ILS) to assist radiation oncology incident learning by semi-automating incident classification. Our go...
Humans Machine Learning Canada Radiation Oncology Natural Language Processing Risk Management
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Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce.

Radiography (London, England : 1995) Sep 4, 2021
OBJECTIVE: Radiation oncology is a continually evolving speciality. With the development of new imaging modalities and advanced imaging processing techniques, there is an increasing amount of data available to practitioners. In this narrative review,...
Workforce Image Processing, Computer-Assisted Radiation Oncology Artificial Intelligence Allied Health Personnel Humans
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Clinical implementation of deep-learning based auto-contouring tools-Experience of three French radiotherapy centers.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique Aug 11, 2021
Deep-learning (DL)-based auto-contouring solutions have recently been proposed as a convincing alternative to decrease workload of target volumes and organs-at-risk (OAR) delineation in radiotherapy planning and improve inter-observer consistency. Ho...
Humans Neoplasms Radiation Oncology Radiotherapy Planning, Computer-Assisted Societies, Medical Workload Deep Learning Practice Guidelines as Topic Radiotherapy, Image-Guided Organs at Risk Europe
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[Artificial intelligence, radiomics and pathomics to predict response and survival of patients treated with radiations].

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique Jul 17, 2021
Artificial intelligence approaches in medicine are more and more used and are extremely promising due to the growing number of data produced and the variety of data they allow to exploit. Thus, the computational analysis of medical images in particul...
Diagnosis, Computer-Assisted Treatment Outcome Radiation Oncology Biomarkers, Tumor Neoplasms Machine Learning Prognosis Humans Artificial Intelligence
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Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care.

JNCI cancer spectrum May 17, 2021
In a time of rapid advances in science and technology, the opportunities for radiation oncology are undergoing transformational change. The linkage between and understanding of the physical dose and induced biological perturbations are opening entire...
Hyperthermia, Induced Big Data Research Humans Radiation Tolerance Neoplasms Radiation Oncology Artificial Intelligence Radiobiology Radiopharmaceuticals Research Support as Topic Clinical Trials as Topic Relative Biological Effectiveness Patient-Centered Care Photochemotherapy Radiotherapy Neutron Capture Therapy
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