AIMC Topic: Technology, Radiologic

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Medical imaging and radiation science students' use of artificial intelligence for learning and assessment.

Radiography (London, England : 1995) Oct 19, 2024
INTRODUCTION: Artificial intelligence has permeated all aspects of our existence, and medical imaging has shown the burgeoning use of artificial intelligence in clinical environments. However, there are limited empirical studies on radiography studen...
Female Students, Medical Male Qualitative Research Humans Artificial Intelligence Learning Curriculum Education, Medical, Undergraduate Focus Groups Technology, Radiologic Educational Measurement Diagnostic Imaging Radiology South Africa
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Evaluating Artificial Intelligence Competency in Education: Performance of ChatGPT-4 in the American Registry of Radiologic Technologists (ARRT) Radiography Certification Exam.

Academic radiology Aug 16, 2024
RATIONALE AND OBJECTIVES: The American Registry of Radiologic Technologists (ARRT) leads the certification process with an exam comprising 200 multiple-choice questions. This study aims to evaluate ChatGPT-4's performance in responding to practice qu...
Clinical Competence Humans Educational Measurement Artificial Intelligence United States Generative Artificial Intelligence Registries Certification Technology, Radiologic
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The American Society of Radiologic Technologists (ASRT) AI educator survey: A cross-sectional study to explore knowledge, experience, and use of AI within education.

Journal of medical imaging and radiation sciences Jul 13, 2024
INTRODUCTION: Artificial Intelligence (AI) is revolutionizing medical imaging and radiation therapy. AI-powered applications are being deployed to aid Medical Radiation Technologists (MRTs) in clinical workflows, decision-making, dose optimisation, a...
Humans Artificial Intelligence Female Cross-Sectional Studies Societies, Medical Technology, Radiologic Male Surveys and Questionnaires United States
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[New Method of Paired Comparison for Improved Observer Shortage Using Deep Learning Models].

Nihon Hoshasen Gijutsu Gakkai zasshi May 17, 2024
PURPOSE: The aim of this study was to validate the potential of substituting an observer in a paired comparison with a deep-learning observer.
Humans Tomography, X-Ray Computed Deep Learning Phantoms, Imaging Technology, Radiologic
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Radiography students' perceptions of artificial intelligence in medical imaging.

Journal of medical imaging and radiation sciences Feb 24, 2024
INTRODUCTION: Education relating to Artificial Intelligence (AI) is becoming critical to developing contemporary radiographers. This study sought to investigate the perceptions of a sample of Australian radiography students regarding AI within the co...
Radiology Technology, Radiologic Surveys and Questionnaires Attitude of Health Personnel Australia Artificial Intelligence Humans Female Young Adult Adult Students, Medical Cross-Sectional Studies Male
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Stopping criteria for ending autonomous, single detector radiological source searches.

PloS one Jun 17, 2021
While the localization of radiological sources has traditionally been handled with statistical algorithms, such a task can be augmented with advanced machine learning methodologies. The combination of deep and reinforcement learning has provided lear...
Machine Learning Bayes Theorem Technology, Radiologic Neural Networks, Computer
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Radiomics: from qualitative to quantitative imaging.

The British journal of radiology Feb 26, 2020
Historically, medical imaging has been a qualitative or semi-quantitative modality. It is difficult to quantify what can be seen in an image, and to turn it into valuable predictive outcomes. As a result of advances in both computational hardware and...
Workflow Technology, Radiologic Brain Neoplasms Male Deep Learning Humans Image Processing, Computer-Assisted Forecasting Lung Neoplasms Female Radiography Breast Neoplasms Diagnostic Imaging
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Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images-Application in Brain Proton Therapy.

International journal of radiation oncology, biology, physics Jul 2, 2019
PURPOSE: The first aim of this work is to present a novel deep convolution neural network (DCNN) multiplane approach and compare it to single-plane prediction of synthetic computed tomography (sCT) by using the real computed tomography (CT) as ground...
Glioblastoma Feasibility Studies Radiotherapy Planning, Computer-Assisted Head Radiotherapy Dosage Air Humans Skull Reproducibility of Results Neural Networks, Computer Brain Neoplasms Proton Therapy Algorithms Magnetic Resonance Imaging Radiotherapy, Image-Guided Multimodal Imaging Technology, Radiologic Tomography, X-Ray Computed
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Development and Validation of a Bayesian Network Method to Detect External Beam Radiation Therapy Physician Order Errors.

International journal of radiation oncology, biology, physics May 31, 2019
PURPOSE: To investigate a Bayesian network (BN)-based method to detect errors in external beam radiation therapy physician orders.
False Negative Reactions False Positive Reactions Radiotherapy Dosage Medical Errors Organ Specificity Humans Neoplasms Radiologists Dose Fractionation, Radiation Radiotherapy Setup Errors Cohort Studies Neural Networks, Computer Radiotherapy Planning, Computer-Assisted Technology, Radiologic ROC Curve Radiotherapy, Image-Guided Algorithms Datasets as Topic Bayes Theorem Simulation Training
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Demystification of AI-driven medical image interpretation: past, present and future.

European radiology Aug 13, 2018
The recent explosion of 'big data' has ushered in a new era of artificial intelligence (AI) algorithms in every sphere of technological activity, including medicine, and in particular radiology. However, the recent success of AI in certain flagship a...
Forecasting Humans Deep Learning Artificial Intelligence Algorithms Radiographic Image Interpretation, Computer-Assisted Technology, Radiologic
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