We are among the many that believe that artificial intelligence will not replace practitioners and is most valuable as an adjunct in diagnostic radiology. We suggest a different approach to utilizing the technology, which may help even radiologists who may be averse to adopting AI. A novel method of leveraging AI combines computer vision and natural language processing to ambiently function in the background, monitoring for critical care gaps.
View Article and Find Full Text PDFObjectives: To evaluate the clinical impact of a deep learning system (DLS) for automated detection of pulmonary nodules on computed tomography (CT) images as a second reader.
Methods: This single-centre retrospective study screened 21,150 consecutive body CT studies from September 2018 to February 2019. Pulmonary nodules detected by the DLS on axial CT images but not mentioned in initial radiology reports were flagged.
J Plast Reconstr Aesthet Surg
February 2013
Background: The increasing incidence of breast cancer is paralleled by an increasing demand for post-mastectomy breast reconstruction. At the time of breast reconstruction routine submission of mastectomy scars has been considered appropriate clinical practice to ensure that no residual cancer exists. However, this practice has been challenged by some and has become the topic of controversy.
View Article and Find Full Text PDFUnlabelled: Studies of hepatitis B virus (HBV)/hepatitis C virus (HCV) dual infection are limited. Most are small, conducted outside the United States, and compare dual infection with HCV monoinfection. The goal of this study was to characterize HBV/HCV dual infection in a large multiethnic, matched, case-control study of dual-infected and HBV-monoinfected patients at two United States centers.
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