AIMC Topic: Radiography

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Towards Data Integration for AI in Cancer Research.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Cancer research is increasing relying on data-driven methods and Artificial Intelligence (AI), to increase accuracy and efficiency in decision making. Such methods can solve a variety of clinically relevant problems in cancer diagnosis and treatment,...
Neoplasms Radiography Diagnostic Imaging Data Collection Humans Artificial Intelligence
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ARTIFICIAL INTELLIGENCE AND DEEP LEARNING IN DIAGNOSTIC RADIOLOGY-IS THIS THE NEXT PHASE OF SCIENTIFIC AND TECHNOLOGICAL DEVELOPMENT?

Radiation protection dosimetry Oct 12, 2021
This paper is concerned with the role of science and technology in helping to create change in society. Diagnostic radiology is an example of an activity that has undergone significant change due to such developments, which over the past 40 years hav...
Machine Learning Deep Learning Radiography Radiology Humans Artificial Intelligence
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Radiomics in Oncology: A Practical Guide.

Radiographics : a review publication of the Radiological Society of North America, Inc Oct 1, 2021
Radiomics refers to the extraction of mineable data from medical imaging and has been applied within oncology to improve diagnosis, prognostication, and clinical decision support, with the goal of delivering precision medicine. The authors provide a ...
Medical Oncology Humans Image Processing, Computer-Assisted Artificial Intelligence Radiography Diagnostic Imaging
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Application of machine learning in CT images and X-rays of COVID-19 pneumonia.

Medicine Sep 10, 2021
Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentation, diagnosis, and evaluation. Artificial intelligence can accurately segment infected parts in X-r...
Radiography Pneumonia, Viral Humans Machine Learning COVID-19 Tomography, X-Ray Computed SARS-CoV-2
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Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms.

The Lancet. Digital health Sep 1, 2021
BACKGROUND: Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-related abnormalities on chest radiographs. Various AI algorithms are available commercially, yet there is little impartial evidence on how their performance...
Artificial Intelligence Algorithms Retrospective Studies Humans Sensitivity and Specificity Male Middle Aged Adolescent Female Young Adult Adult Bangladesh Radiologists ROC Curve Radiographic Image Interpretation, Computer-Assisted Triage Tuberculosis, Pulmonary Radiography
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Artificial Intelligence in COVID-19 Imaging Mismatched to the Clinic.

JAMA Jul 13, 2021
Humans Artificial Intelligence COVID-19 Lung Ultrasonography Radiography
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Can a Deep-learning Model for the Automated Detection of Vertebral Fractures Approach the Performance Level of Human Subspecialists?

Clinical orthopaedics and related research Jul 1, 2021
BACKGROUND: Vertebral fractures are the most common osteoporotic fractures in older individuals. Recent studies suggest that the performance of artificial intelligence is equal to humans in detecting osteoporotic fractures, such as fractures of the h...
Osteoporotic Fractures Observer Variation Absorptiometry, Photon Spinal Fractures Thoracic Vertebrae Radiography Lumbar Vertebrae Reproducibility of Results Humans Aged Retrospective Studies Aged, 80 and over Sensitivity and Specificity Deep Learning Female Male ROC Curve
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Deep Learning Automates Measurement of Spinopelvic Parameters on Lateral Lumbar Radiographs.

Spine Jun 15, 2021
STUDY DESIGN: Cross-sectional database study.
Radiographic Image Interpretation, Computer-Assisted Lumbar Vertebrae Lumbosacral Region Algorithms Deep Learning Radiography Humans
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A deep learning approach to dental restoration classification from bitewing and periapical radiographs.

Quintessence international (Berlin, Germany : 1985) Jun 9, 2021
OBJECTIVE: The aim of this study was to examine the success of deep learning-based convolutional neural networks (CNN) in the detection and differentiation of amalgam, composite resin, and metal-ceramic restorations from bitewing and periapical radio...
Radiography Humans Deep Learning Composite Resins Neural Networks, Computer ROC Curve
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Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study.

The Lancet. Digital health Jun 1, 2021
BACKGROUND: The tumour stroma microenvironment plays an important part in disease progression and its composition can influence treatment response and outcomes. Histological evaluation of tumour stroma is limited by access to tissue, spatial heteroge...
Radiography Progression-Free Survival Disease-Free Survival Stomach Neoplasms Retrospective Studies ROC Curve Proportional Hazards Models Biomarkers, Tumor Predictive Value of Tests Humans Middle Aged Tomography, X-Ray Computed Stomach Male Area Under Curve Neural Networks, Computer Female Deep Learning Prognosis Chemotherapy, Adjuvant China
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