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http://dx.doi.org/10.1001/jamainternmed.2024.2676 | DOI Listing |
Neural Netw
September 2025
School of Electronic Science and Engineering, Nanjing University, China. Electronic address:
The Segment Anything Model (SAM) is a cornerstone of image segmentation, demonstrating exceptional performance across various applications, particularly in autonomous driving and medical imaging, where precise segmentation is crucial. However, SAM is vulnerable to adversarial attacks that can significantly impair its functionality through minor input perturbations. Traditional techniques, such as FGSM and PGD, are often ineffective in segmentation tasks due to their reliance on global perturbations that overlook spatial nuances.
View Article and Find Full Text PDFNeural Netw
September 2025
Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China. Electronic address:
Automatic segmentation of retinal vessels from retinography images is crucial for timely clinical diagnosis. However, the high cost and specialized expertise required for annotating medical images often result in limited labeled datasets, which constrains the full potential of deep learning methods. Recent advances in self-supervised pretraining using unlabeled data have shown significant benefits for downstream tasks.
View Article and Find Full Text PDFNeural Netw
September 2025
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China.
3D shape defect detection plays an important role in autonomous industrial inspection. However, accurate detection of anomalies remains challenging due to the complexity of multimodal sensor data, especially when both color and structural information are required. In this work, we propose a lightweight inter-modality feature prediction framework that effectively utilizes multimodal fused features from the inputs of RGB, depth and point clouds for efficient 3D shape defect detection.
View Article and Find Full Text PDFJMIR Ment Health
September 2025
Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Box 951563, Los Angeles, CA, 90095, United States, 1 3107941262.
Background: Youth mental health issues have been recognized as a pressing crisis in the United States in recent years. Effective, evidence-based mental health research and interventions require access to integrated datasets that consolidate diverse and fragmented data sources. However, researchers face challenges due to the lack of centralized, publicly available datasets, limiting the potential for comprehensive analysis and data-driven decision-making.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
School of Governance and Policy Science, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong).
Background: Older adults are more vulnerable to severe consequences caused by seasonal influenza. Although seasonal influenza vaccination (SIV) is effective and free vaccines are available, the SIV uptake rate remained inadequate among people aged 65 years or older in Hong Kong, China. There was a lack of studies evaluating ChatGPT in promoting vaccination uptake among older adults.
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