A new technique has been developed to identify ACL tears in sports injuries. This method utilizes a Convolutional Neural Network (CNN) in combination with a modified Political Optimizer (IPO) algorithm, resulting in a major breakthrough in detecting ...
Wearable devices face a significant challenge in balancing battery life with performance, often leading to frequent recharging and reduced user satisfaction. In this paper, we introduce the SmartAPM (Smart Adaptive Power Management) framework, a nove...
Computer-aided automatic brain tumor detection is crucial for timely diagnosis and treatment, especially in regions with limited access to medical expertise. However, existing methods often overlook edge pixel information during tumor segmentation, l...
OBJECTIVE: This study developed and validated a stacked ensemble machine learning model to predict the risk of acute kidney injury in patients with acute pancreatitis complicated by sepsis.
BACKGROUND: Sepsis is an organ dysfunction caused by a dysregulated host response to infection. Early detection is fundamental to improving the patient outcome. Laboratory medicine can play a crucial role by providing biomarkers whose alteration can ...
This paper introduces a novel control strategy for managing the uncertainties in flexible joint manipulators, incorporating a Radial Basis Function Neural Network (RBFNN) with Adaptive Dynamic Surface Control (ADSC). This strategy innovatively utiliz...
With the dramatic increase in the number of published papers and the continuous progress of deep learning technology, the research on name disambiguation is at a historic peak, the number of paper authors is increasing every year, and the situation o...
More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant o...
Journal of evidence-based social work (2019)
Feb 26, 2025
PURPOSE: Artificial Intelligence (AI) technologies are rapidly expanding across diverse contexts. As the reach of AI continues to grow, there is a need to examine student perspectives on the increasing prevalence of AI and AI-based practice approache...
Machine learning has emerged as a crucial tool for medical image analysis, largely due to recent developments in deep artificial neural networks addressing numerous, diverse clinical problems. As with any conceptual tool, the effective use of machine...
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