Journal of the American College of Radiology : JACR
Jun 4, 2019
PURPOSE: Radiology-pathology correlation has long been foundational to continuing education, peer learning, quality assurance, and multidisciplinary patient care. The objective of this study was to determine whether modern deep-learning language-mode...
Background Risk stratification systems for thyroid nodules are often complicated and affected by low specificity. Continual improvement of these systems is necessary to reduce the number of unnecessary thyroid biopsies. Purpose To use artificial inte...
Avascular Necrosis (AN) is a cause of muscular-skeletal disability. As it is common amongst the younger people, early intervention and prompt diagnosis is requisite. This disease normally affects the femoral bones, in order that the bones' shape gets...
Originally motivated by the need for research reproducibility and data reuse, large-scale, open access information repositories have become key resources for training and testing of advanced machine learning applications in biomedical and clinical re...
Journal of the American College of Radiology : JACR
Mar 2, 2019
OBJECTIVE: Radiology is a finite health care resource in high demand at most health centers. However, anticipating fluctuations in demand is a challenge because of the inherent uncertainty in disease prognosis. The aim of this study was to explore th...
The classification of medical images is an essential task in computer-aided diagnosis, medical image retrieval and mining. Although deep learning has shown proven advantages over traditional methods that rely on the handcrafted features, it remains c...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Reviewing radiology reports in emergency departments is an essential but laborious task. Timely follow-up of patients with abnormal cases in their radiology reports may dramatically affect the patient's outcome, especially if they have been discharge...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
We propose a scalable computerized approach for large-scale inference of Liver Imaging Reporting and Data System (LI-RADS) final assessment categories in narrative ultrasound (US) reports. Although our model was trained on reports created using a LI-...
Radiology images are an essential part of clinical decision making and population screening, e.g., for cancer. Automated systems could help clinicians cope with large amounts of images by answering questions about the image contents. An emerging area...
BACKGROUND: There is interest in using convolutional neural networks (CNNs) to analyze medical imaging to provide computer-aided diagnosis (CAD). Recent work has suggested that image classification CNNs may not generalize to new data as well as previ...
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