AIMC Topic: Radiology

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Use of BERT (Bidirectional Encoder Representations from Transformers)-Based Deep Learning Method for Extracting Evidences in Chinese Radiology Reports: Development of a Computer-Aided Liver Cancer Diagnosis Framework.

Journal of medical Internet research Jan 12, 2021
BACKGROUND: Liver cancer is a substantial disease burden in China. As one of the primary diagnostic tools for detecting liver cancer, dynamic contrast-enhanced computed tomography provides detailed evidences for diagnosis that are recorded in free-te...
Diagnosis, Computer-Assisted Deep Learning Humans Natural Language Processing Radiology Information Storage and Retrieval China Liver Neoplasms
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Artificial intelligence in radiology: relevance of collaborative work between radiologists and engineers for building a multidisciplinary team.

Clinical radiology Dec 23, 2020
The use of artificial intelligence (AI) algorithms in the field of radiology is becoming more common. Several studies have demonstrated the potential utility of machine learning (ML) and deep learning (DL) techniques as aids for radiologists to solve...
Interdisciplinary Research Interprofessional Relations Engineering Humans Artificial Intelligence Equipment Design Radiologists Radiology
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Analysis of Stroke Detection during the COVID-19 Pandemic Using Natural Language Processing of Radiology Reports.

AJNR. American journal of neuroradiology Dec 17, 2020
BACKGROUND AND PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic has led to decreases in neuroimaging volume. Our aim was to quantify the change in acute or subacute ischemic strokes detected on CT or MR imaging during the pandemic using natu...
Middle Aged Cohort Studies SARS-CoV-2 Male Stroke Neuroimaging Natural Language Processing Radiology Machine Learning COVID-19 Retrospective Studies Female Humans
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Domain specific word embeddings for natural language processing in radiology.

Journal of biomedical informatics Dec 15, 2020
BACKGROUND: There has been increasing interest in machine learning based natural language processing (NLP) methods in radiology; however, models have often used word embeddings trained on general web corpora due to lack of a radiology-specific corpus...
Unified Medical Language System Radiology Semantics Machine Learning Natural Language Processing
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Proposals for the use of artificial intelligence in emergency radiology.

Diagnostic and interventional imaging Dec 2, 2020
Radiology Humans Artificial Intelligence Radiography
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Medicolegal considerations of radiology report writing in the new pjmirodigm of artificial intelligence.

Journal of medical imaging and radiation oncology Nov 20, 2020
Radiologists Writing Humans Radiology Artificial Intelligence
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Machine learning in cardiovascular radiology: ESCR position statement on design requirements, quality assessment, current applications, opportunities, and challenges.

European radiology Nov 19, 2020
Machine learning offers great opportunities to streamline and improve clinical care from the perspective of cardiac imagers, patients, and the industry and is a very active scientific research field. In light of these advances, the European Society o...
Humans Machine Learning Radiology Societies, Medical Algorithms Radiography
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Artificial Intelligence and Big Data.

Klinische Monatsblatter fur Augenheilkunde Nov 19, 2020
Medical images play an important role in ophthalmology and radiology. Medical image analysis has greatly benefited from the application of "deep learning" techniques in clinical and experimental radiology. Clinical applications and their relevance fo...
Radiology Ophthalmology Artificial Intelligence Deep Learning Big Data
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Artificial intelligence in oral and maxillofacial radiology: what is currently possible?

Dento maxillo facial radiology Nov 16, 2020
Artificial intelligence, which has been actively applied in a broad range of industries in recent years, is an active area of interest for many researchers. Dentistry is no exception to this trend, and the applications of artificial intelligence are ...
Radiology Radiologists Artificial Intelligence Radiography Humans Neural Networks, Computer
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Potential use of deep learning techniques for postmortem imaging-moving beyond postmortem radiology.

Forensic science, medicine, and pathology Nov 11, 2020
Humans Deep Learning Radiology Autopsy Radiography Diagnostic Imaging
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