AIMC Topic: Radiology
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Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging.
Breast cancer research and treatment
Feb 4, 2020
BACKGROUND AND PURPOSE: Multiparametric radiological imaging is vital for detection, characterization, and diagnosis of many different diseases. Radiomics provide quantitative metrics from radiological imaging that may infer potential biological mean...
Artificial intelligence: Who is responsible for the diagnosis?
La Radiologia medica
Jan 31, 2020
The aim of the paper is to find an answer to the question "Who or what is responsible for the benefits and harms of using artificial intelligence in radiology?" When human beings make decisions, the action itself is normally connected with a direct r...
Deep Learning for Natural Language Processing in Radiology-Fundamentals and a Systematic Review.
Journal of the American College of Radiology : JACR
Jan 28, 2020
PURPOSE: Natural language processing (NLP) enables conversion of free text into structured data. Recent innovations in deep learning technology provide improved NLP performance. We aimed to survey deep learning NLP fundamentals and review radiology-r...
Artificial Intelligence in Radiology Residency Training.
Seminars in musculoskeletal radiology
Jan 28, 2020
Artificial intelligence (AI) is an emerging technology that brings a wide array of new tools to the field of radiology. AI will certainly have an impact on the day-to-day work of radiologists in the coming decades, thus training programs must prepare...
From Data to Value: How Artificial Intelligence Augments the Radiology Business to Create Value.
Seminars in musculoskeletal radiology
Jan 28, 2020
The radiology practice has access to a wealth of data in the radiologist information system, dictation reports, and electronic health records. Although many artificial intelligence applications in radiology have focused on computer vision and the int...
Top 10 Reviewer Critiques of Radiology Artificial Intelligence (AI) Articles: Qualitative Thematic Analysis of Reviewer Critiques of Machine Learning/Deep Learning Manuscripts Submitted to JMRI.
Journal of magnetic resonance imaging : JMRI
Jan 13, 2020
BACKGROUND: Classical machine learning (ML) and deep learning (DL) articles have rapidly captured the attention of the radiology research community and comprise an increasing proportion of articles submitted to JMRI, of variable reporting and methodo...
Editorial for "Top 10 Reviewer Critiques of Radiology Artificial Intelligence (AI) Articles: Qualitative Thematic Analysis of Reviewer Critiques of Machine Learning / Deep Learning Manuscripts Submitted to JMRI".
Journal of magnetic resonance imaging : JMRI
Jan 10, 2020
Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers-From the Editorial Board.
Radiology
Dec 31, 2019
Artificial intelligence in medical imaging.
Magnetic resonance imaging
Dec 16, 2019
The medical specialty radiology has experienced a number of extremely important and influential technical developments in the past that have affected how medical imaging is deployed. Artificial intelligence (AI) is potentially another such developmen...
Artificial intelligence in diagnostic imaging: impact on the radiography profession.
The British journal of radiology
Dec 16, 2019
The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radio...
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