Advances in radiomics and machine learning have driven a technology boom in the automated analysis of radiology images. For the past several years, expectations have been nearly boundless for these new technologies to revolutionize radiology image an...
PURPOSE: Although the bulk of patient-generated health data are increasing exponentially, their use is impeded because most data come in unstructured format, namely as free-text clinical reports. A variety of natural language processing (NLP) methods...
Journal of the American College of Radiology : JACR
Apr 1, 2019
Commercially available artificial intelligence (AI) algorithms outside of health care have been shown to be susceptible to ethnic, gender, and social bias, which has important implications in the development of AI algorithms in health care and the ra...
Gan to kagaku ryoho. Cancer & chemotherapy
Mar 1, 2019
Artificial intelligence has attracted attention in the various field as an advanced information technology. Regarding to the radiology, many artificial intelligence technologies have been introduced to the computer aided diagnosis technologies such a...
Academic medicine : journal of the Association of American Medical Colleges
Mar 1, 2019
PURPOSE: To identify the different machine learning (ML) techniques that have been applied to automate physician competence assessment and evaluate how these techniques can be used to assess different competence domains in several medical specialties...
In today's radiology workflow, free-text reporting is established as the most common medium to capture, store, and communicate clinical information. Radiologists routinely refer to prior radiology reports of a patient to recall critical information f...
Annals of the Academy of Medicine, Singapore
Jan 1, 2019
Artificial intelligence (AI) has been positioned as being the most important recent advancement in radiology, if not the most potentially disruptive. Singapore radiologists have been quick to embrace this technology as part of the natural progression...