The efficacy of convolutional neural network (CNN)-enhanced electrocardiography (ECG) in detecting hypertrophic cardiomyopathy (HCM) and dilated HCM (dHCM) remains uncertain in real-world applications. This retrospective study analyzed data from 19,1...
ASAIO journal (American Society for Artificial Internal Organs : 1992)
Mar 29, 2024
In kidney transplantation, pairing recipients with the highest longevity with low-risk allografts to optimize graft-donor survival is a complex challenge. Current risk prediction models exhibit limited discriminative and calibration capabilities and ...
BACKGROUND AND OBJECTIVES: Cervical disk arthroplasty (CDA) offers the advantage of motion preservation in the treatment of focal cervical pathology. At present, implant sizing is performed using subjective tactile feedback and imaging of trial cages...
OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and long-term functional outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) remain uncertain. Here, the authors apply their recently devel...
The journal of trauma and acute care surgery
Mar 29, 2024
BACKGROUND: The optimal management of blunt thoracic aortic injury (BTAI) remains controversial, with experienced centers offering therapy ranging from medical management to TEVAR. We investigated the utility of a machine learning (ML) algorithm to d...
AIM: We aimed to investigate the efficiency and accuracy of an artificial intelligence (AI) algorithm for detecting interval cancers in a middle-income country's national screening program.
OBJECTIVE: Achieving appropriate spinopelvic alignment has been shown to be associated with improved clinical symptoms. However, measurement of spinopelvic radiographic parameters is time-intensive and interobserver reliability is a concern. Automate...
An intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&E) histology, such as frozen section, are time-, resource-, and labor-intensive, and involve specime...
BACKGROUND: Diabetic neuropathy is one of the most common complications of diabetes mellitus. The aim of this study is to evaluate the Moveo device, a novel device that uses a machine learning (ML) algorithm to detect and track diabetic neuropathy. T...
Journal of imaging informatics in medicine
Mar 28, 2024
We proposed an end-to-end deep learning convolutional neural network (DCNN) for region-of-interest based multi-parameter quantification (RMQ-Net) to accelerate quantitative ultrashort echo time (UTE) MRI of the knee joint with automatic multi-tissue ...
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