AIMC Topic: Radiation Oncology
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Deep Learning in Radiation Oncology Treatment Planning for Prostate Cancer: A Systematic Review.
Journal of medical systems
Aug 30, 2020
Radiation oncology for prostate cancer is important as it can decrease the morbidity and mortality associated with this disease. Planning for this modality of treatment is both fundamental, time-consuming and prone to human-errors, leading to potenti...
Artificial intelligence and soft skills in radiation oncology: Data versus wisdom.
Journal of medical imaging and radiation sciences
Aug 25, 2020
Artificial intelligence in radiation oncology.
Nature reviews. Clinical oncology
Aug 25, 2020
Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is practised. AI platforms excel in recognizing complex patterns in medical data and provide a quantitative, rather than purely qualitative, assessment of clinical...
Comparison of CBCT-based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning.
Medical physics
Aug 11, 2020
PURPOSE: Anatomical variations occur during head and neck (H&N) radiotherapy treatment. kV cone-beam computed tomography (CBCT) images can be used for daily dose monitoring to assess dose variations owing to anatomic changes. Deep learning methods (D...
Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives.
Methods (San Diego, Calif.)
Jul 19, 2020
Radiation therapy is a pivotal cancer treatment that has significantly progressed over the last decade due to numerous technological breakthroughs. Imaging is now playing a critical role on deployment of the clinical workflow, both for treatment plan...
Radiomics in radiation oncology-basics, methods, and limitations.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Jul 9, 2020
Over the past years, the quantity and complexity of imaging data available for the clinical management of patients with solid tumors has increased substantially. Without the support of methods from the field of artificial intelligence (AI) and machin...
Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
May 11, 2020
BACKGROUND: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use o...
DNA Repair Enzymes
Deep Learning
Image Processing, Computer-Assisted
Tumor Suppressor Proteins
Computational Biology
Glioma
Diagnosis, Differential
Neuroimaging
Humans
Magnetic Resonance Imaging
Glioblastoma
Neoplasm Proteins
Isocitrate Dehydrogenase
Sensitivity and Specificity
DNA Methylation
Radiation Oncology
Imaging Genomics
Brain Neoplasms
Neoplasm Grading
Positron-Emission Tomography
Neoplasm Recurrence, Local
Radiotherapy Planning, Computer-Assisted
Progression-Free Survival
DNA Modification Methylases
Radiosurgery
Promoter Regions, Genetic
Artificial intelligence radiogenomics for advancing precision and effectiveness in oncologic care (Review).
International journal of oncology
May 11, 2020
The new era of artificial intelligence (AI) has introduced revolutionary data‑driven analysis paradigms that have led to significant advancements in information processing techniques in the context of clinical decision‑support systems. These advances...
Ontologies in radiation oncology.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 2, 2020
Ontologies are a formal, computer-compatible method for representing scientific knowledge about a given domain. They provide a standardized vocabulary, taxonomy and set of relations between concepts. When formatted in a standard way, they can be read...
The Impact of Artificial Intelligence and Machine Learning in Radiation Therapy: Considerations for Future Curriculum Enhancement.
Journal of medical imaging and radiation sciences
Feb 27, 2020
Artificial intelligence (AI) and machine learning (ML) approaches have caught the attention of many in health care. Current literature suggests there are many potential benefits that could transform future clinical workflows and decision making. Embe...
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