Dual-energy X-ray absorptiometry (DXA) is underutilized to measure bone mineral density (BMD) and evaluate fracture risk. We present an automated tool to identify fractures, predict BMD, and evaluate fracture risk using plain radiographs. The tool pe...
AJR. American journal of roentgenology
Sep 15, 2021
Shoulder MRI using standard multiplanar sequences requires long scan times. Accelerated sequences have tradeoffs in noise and resolution. Deep learning-based reconstruction (DLR) may allow reduced scan time with preserved image quality. The purpose...
Decision making on the treatment of vestibular schwannoma (VS) is mainly based on the symptoms, tumor size, patient's preference, and experience of the medical team. Here we provide objective tools to support the decision process by answering two que...
Our aim was to investigate the usefulness of machine learning approaches on linked administrative health data at the population level in predicting older patients' one-year risk of acute coronary syndrome and death following the use of non-steroidal ...
BACKGROUND: It is important to improve verbal Working Memory (WM) in reading disability, as it is a key factor in learning. There are commercial verbal WM training programs, which have some short-term effects only on the verbal WM capacity, not readi...
The giant gourami sago strain ( Lacepède) has been approved in 2018 as a candidate for freshwater aquaculture in Indonesia. However, information on the species' reproduction is minimal. This study analyzed the reproductive characteristics of the go...
Deep neural networks (DNNs) that predict mutational status from H&E slides of cancers can enable inexpensive and timely precision oncology. Although expert knowledge is reliable for annotating regions informative of malignancy and other known histolo...
BACKGROUND AND OBJECTIVE: To test the hypothesis that a multicenter-validated computer deep learning algorithm detects MRI-negative focal cortical dysplasia (FCD).
OBJECTIVES: For optimal utilization of healthcare resources, there is a critical need for early identification of COVID-19 patients at risk of poor prognosis as defined by the need for intensive unit care and mechanical ventilation. We tested the fea...
Artificial intelligence technology is becoming more prevalent in health care as a tool to improve practice patterns and patient outcomes. This study assessed ability of a commercialized artificial intelligence (AI) mobile application to identify and ...
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