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Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography.
Diagnostic and interventional imaging
Oct 4, 2024
PURPOSE: The purpose of this study was to evaluate the diagnostic performance of automated deep learning in the detection of coronary artery disease (CAD) on photon-counting coronary CT angiography (PC-CCTA).
Clinical Impact of Radiologist's Alert System on Patient Care for High-risk Incidental CT Findings: A Machine Learning-Based Risk Factor Analysis.
Academic radiology
Oct 4, 2024
RATIONALE AND OBJECTIVES: Efficient communication between radiologists and clinicians ordering computed tomography (CT) examinations is crucial for managing high-risk incidental CT findings (ICTFs). Herein, we introduced a Radiologist's Alert and Pat...
Effects of end-effector robotic arm reach training with functional electrical stimulation for chronic stroke survivors.
Topics in stroke rehabilitation
Oct 3, 2024
BACKGROUND: Upper-extremity dysfunction significantly affects dependence in the daily lives of stroke survivors, limiting their participation in the social environment and reducing their quality of life.
Construction and validation of a nomogram prediction model for the catheter-related thrombosis risk of central venous access devices in patients with cancer: a prospective machine learning study.
Journal of thrombosis and thrombolysis
Oct 3, 2024
Central venous access devices (CVADs) are integral to cancer treatment. However, catheter-related thrombosis (CRT) poses a considerable risk to patient safety. It interrupts treatment; delays therapy; prolongs hospitalisation; and increases the physi...
Prognostic insights after surgery for advances in understanding signet ring cell gastric cancer: a machine learning approach.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Oct 3, 2024
BACKGROUND: Signet ring cell (SRC) gastric carcinoma is traditionally associated with a poor prognosis. However, the literature has presented contradictory results. Linear models are the standard statistical tools typically used to study these condit...
Machine learning model to predict early recurrence in patients with perihilar cholangiocarcinoma planned treatment with curative resection: a multicenter study.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Oct 3, 2024
BACKGROUND: Early recurrence is the leading cause of death for patients with perihilar cholangiocarcinoma (pCCA) after surgery. Identifying high-risk patients preoperatively is important. This study aimed to construct a preoperative prediction model ...
Deep learning predicted perceived age is a reliable approach for analysis of facial ageing: A proof of principle study.
Journal of the European Academy of Dermatology and Venereology : JEADV
Oct 3, 2024
BACKGROUND: Perceived age (PA) has been associated with mortality, genetic variants linked to ageing and several age-related morbidities. However, estimating PA in large datasets is laborious and costly to generate, limiting its practical applicabili...
A radiographic artificial intelligence tool to identify candidates suitable for partial knee arthroplasty.
Archives of orthopaedic and trauma surgery
Oct 3, 2024
INTRODUCTION: Knee osteoarthritis is a prevalent condition frequently necessitating knee replacement surgery, with demand projected to rise substantially. Partial knee arthroplasty (PKA) offers advantages over total knee arthroplasty (TKA), yet its u...
Estimating the prevalence of select non-communicable diseases in Saudi Arabia using a population-based sample: econometric analysis with natural language processing.
Annals of Saudi medicine
Oct 3, 2024
BACKGROUND: Non-communicable diseases (NCDs) are a major public health challenge globally, including in Saudi Arabia. However, measuring the true extent of NCD prevalence has been hampered by a paucity of nationally representative epidemiological stu...
Automated Neural Architecture Search for Cardiac Amyloidosis Classification from [18F]-Florbetaben PET Images.
Journal of imaging informatics in medicine
Oct 2, 2024
Medical image classification using convolutional neural networks (CNNs) is promising but often requires extensive manual tuning for optimal model definition. Neural architecture search (NAS) automates this process, reducing human intervention signifi...
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