AIMC Topic: Image Interpretation, Computer-Assisted
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Clinical application of artificial intelligence-assisted diagnosis using anteroposterior pelvic radiographs in children with developmental dysplasia of the hip.
The bone & joint journal
Nov 1, 2020
AIMS: The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an effective diagnostic tool for DDH. Here, we aimed to develop an an...
Overview of Machine Learning Part 1: Fundamentals and Classic Approaches.
Neuroimaging clinics of North America
Nov 1, 2020
The extensive body of research and advances in machine learning (ML) and the availability of a large volume of patient data make ML a powerful tool for producing models with the potential for widespread deployment in clinical settings. This article p...
Artificial Intelligence Applications for Workflow, Process Optimization and Predictive Analytics.
Neuroimaging clinics of North America
Nov 1, 2020
There is great potential for artificial intelligence (AI) applications, especially machine learning and natural language processing, in medical imaging. Much attention has been garnered by the image analysis tasks for diagnostic decision support and ...
Machine Learning Applications for Head and Neck Imaging.
Neuroimaging clinics of North America
Nov 1, 2020
The head and neck (HN) consists of a large number of vital anatomic structures within a compact area. Imaging plays a central role in the diagnosis and management of major disorders affecting the HN. This article reviews the recent applications of ma...
An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 2: Ischemic Stroke Imaging and Triage.
Neuroimaging clinics of North America
Nov 1, 2020
Acute ischemic stroke constitutes approximately 85% of strokes. Most strokes occur in community settings; thus, automatic algorithms techniques are attractive for managing these cases. This article reviews the use of deep learning convolutional neura...
Review of Natural Language Processing in Radiology.
Neuroimaging clinics of North America
Nov 1, 2020
Natural language processing (NLP) is an interdisciplinary field, combining linguistics, computer science, and artificial intelligence to enable machines to read and understand human language for meaningful purposes. Recent advancements in deep learni...
Machine Learning Algorithm Validation: From Essentials to Advanced Applications and Implications for Regulatory Certification and Deployment.
Neuroimaging clinics of North America
Nov 1, 2020
The deployment of machine learning (ML) models in the health care domain can increase the speed and accuracy of diagnosis and improve treatment planning and patient care. Translating academic research to applications that are deployable in clinical s...
Regularized Bagged Canonical Component Analysis for Multiclass Learning in Brain Imaging.
Neuroinformatics
Oct 1, 2020
A fundamental problem of supervised learning algorithms for brain imaging applications is that the number of features far exceeds the number of subjects. In this paper, we propose a combined feature selection and extraction approach for multiclass pr...
Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis.
World journal of gastroenterology
Sep 14, 2020
BACKGROUND: Efforts should be made to develop a deep-learning diagnosis system to distinguish pancreatic cancer from benign tissue due to the high morbidity of pancreatic cancer.
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