AIMC Topic: Radiography
Clear Filters Showing 621 to 630 of 1088 articles
Radiomics: a primer on high-throughput image phenotyping.
Abdominal radiology (New York)
Aug 25, 2021
Radiomics is a high-throughput approach to image phenotyping. It uses computer algorithms to extract and analyze a large number of quantitative features from radiological images. These radiomic features collectively describe unique patterns that can ...
A deep learning-machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors.
European radiology
Aug 25, 2021
OBJECTIVES: To build and validate deep learning and machine learning fusion models to classify benign, malignant, and intermediate bone tumors based on patient clinical characteristics and conventional radiographs of the lesion.
Artificial intelligence: The opinions of radiographers and radiation therapists in Ireland.
Radiography (London, England : 1995)
Aug 25, 2021
INTRODUCTION: Implementation of Artificial Intelligence (AI) into medical imaging is much debated. Diagnostic Radiographers (DRs) and Radiation Therapists (RTTs) are at the forefront of this technological leap, thus an understanding of their views, i...
On the Use of Deep Learning for Imaging-Based COVID-19 Detection Using Chest X-rays.
Sensors (Basel, Switzerland)
Aug 24, 2021
The global COVID-19 pandemic that started in 2019 and created major disruptions around the world demonstrated the imperative need for quick, inexpensive, accessible and reliable diagnostic methods that would allow the detection of infected individual...
Artificial Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by the Society of Radiographers AI working group.
Radiography (London, England : 1995)
Aug 20, 2021
INTRODUCTION: Artificial intelligence (AI) has started to be increasingly adopted in medical imaging and radiotherapy clinical practice, however research, education and partnerships have not really caught up yet to facilitate a safe and effective tra...
Effect of Patient Clinical Variables in Osteoporosis Classification Using Hip X-rays in Deep Learning Analysis.
Medicina (Kaunas, Lithuania)
Aug 20, 2021
: A few deep learning studies have reported that combining image features with patient variables enhanced identification accuracy compared with image-only models. However, previous studies have not statistically reported the additional effect of pati...
Qualifying Certainty in Radiology Reports through Deep Learning-Based Natural Language Processing.
AJNR. American journal of neuroradiology
Aug 19, 2021
BACKGROUND AND PURPOSE: Communication gaps exist between radiologists and referring physicians in conveying diagnostic certainty. We aimed to explore deep learning-based bidirectional contextual language models for automatically assessing diagnostic ...
Professionals' responses to the introduction of AI innovations in radiology and their implications for future adoption: a qualitative study.
BMC health services research
Aug 14, 2021
BACKGROUND: Artificial Intelligence (AI) innovations in radiology offer a potential solution to the increasing demand for imaging tests and the ongoing workforce crisis. Crucial to their adoption is the involvement of different professional groups, n...
Impact of artificial intelligence on clinical radiography practice: Futuristic prospects in a low resource setting.
Radiography (London, England : 1995)
Aug 13, 2021
OBJECTIVES: Current trends in clinical radiography practice include the integration of artificial intelligence (AI) and related applications to improve patient care and enhance research. However, in low resource countries there are unique barriers to...
Optimal number of strong labels for curriculum learning with convolutional neural network to classify pulmonary abnormalities in chest radiographs.
Computers in biology and medicine
Aug 9, 2021
BACKGROUND AND OBJECTIVE: It is important to alleviate annotation efforts and costs by efficiently training on medical images. We performed a stress test on several strong labels for curriculum learning with a convolutional neural network to differen...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31239
- Neural Networks, Computer 29811
- Algorithms 26949
- Deep Learning 26474
- Artificial Intelligence 24398
- Robotics 13325
- Image Processing, Computer-Assisted 9569
- Retrospective Studies 9150
- Magnetic Resonance Imaging 6209
- Reproducibility of Results 5604
- Tomography, X-Ray Computed 4787
- Support Vector Machine 4702
- Computational Biology 4259
- Brain 4057
- Computer Simulation 3888
Recent Journals
- Scientific reports 6162
- Sensors (Basel, Switzerland) 4794
- PloS one 4061
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1868
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1141
- Journal of chemical information and modeling 1016
- Nature communications 968
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 863
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 830