PURPOSE: To achieve prenatal prediction of placenta accreta spectrum (PAS) by combining clinical model, radiomics model, and deep learning model using T2-weighted images (T2WI), and to objectively evaluate the performance of the prediction through mu...
OBJECTIVE: To compare the accuracy, efficiency, and safety of robotic assistance (RA) and conventional fluoroscopy guidance for the placement of C1 lateral mass and C2 pedicle screws in posterior atlantoaxial fusion.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Sep 10, 2022
OBJECTIVES: Automated image-level detection of large vessel occlusions (LVO) could expedite patient triage for mechanical thrombectomy. A few studies have previously attempted LVO detection using artificial intelligence (AI) on CT angiography (CTA) i...
PURPOSE: The accuracy of lymph node (LN) dissection in robotic surgery for lung cancer remains controversial. We compared the accuracy of LN dissection in robot-assisted thoracic surgery (RATS) vs. video-assisted thoracic surgery (VATS).
Clinical orthopaedics and related research
Sep 9, 2022
BACKGROUND: Missed fractures are the most common diagnostic errors in musculoskeletal imaging and can result in treatment delays and preventable morbidity. Deep learning, a subfield of artificial intelligence, can be used to accurately detect fractur...
OBJECTIVE: Spinal robotics for thoracolumbar procedures, predominantly employed for the insertion of pedicle screws, is currently an emerging topic in the literature. The use of robotics in instrumentation of the cervical spine has not been broadly e...
BACKGROUND: With the emergence of the concept of value-based care, efficient resource allocation has become an increasingly prominent factor in surgical decision-making. Validated machine learning (ML) models for cost prediction in outpatient spine s...
The analytic procedures incorporated to facilitate the delivery of projects are often referred to as project analytics. Existing techniques focus on retrospective reporting and understanding the underlying relationships to make informed decisions. Al...
IEEE journal of biomedical and health informatics
Sep 9, 2022
Around 60-80% of radiological errors are attributed to overlooked abnormalities, the rate of which increases at the end of work shifts. In this study, we run an experiment to investigate if artificial intelligence (AI) can assist in detecting radiolo...
PURPOSE: To compare the reader performance of artificial intelligence computer-aided detection synthesized mammograms (AI CAD SM) with that of digital mammograms (DM) when used alone or in combination with digital breast tomosynthesis (DBT) images.
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