According to statistics released by the WHO, China has the highest prevalence of myopia in the world, with a frequency that is 1.5 times higher than the global average. Asians have the highest prevalence of myopia worldwide. The Ministry of Education and the State General Administration of Sports "2010 National Student Physical Fitness and Health Research Results" show that the incidence of poor vision among primary and secondary school students in China is 67.3%, and elementary school students' vision has decreased by 40.9%. Low vision among youth has become a major cause of affecting the quality of the population and improving national physical fitness; therefore, how to improve and enhance the vision level of youth has become a major issue for the government, sports, and educators face as a major issue. In order to address this issue, this research suggests a deep learning-based vision monitoring and risk prediction model for high myopia eyes and develops a deep artificial neural network that unsupervised learns essential characteristics of physiological time-series data.
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http://dx.doi.org/10.1155/2022/4537021 | DOI Listing |
Neuroimage
January 2025
Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea. Electronic address:
Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact.
View Article and Find Full Text PDFComput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.
View Article and Find Full Text PDFComput Biol Med
January 2025
School of Computer Science, Chungbuk National University, Cheongju 28644, Republic of Korea. Electronic address:
The fusion index is a critical metric for quantitatively assessing the transformation of in vitro muscle cells into myotubes in the biological and medical fields. Traditional methods for calculating this index manually involve the labor-intensive counting of numerous muscle cell nuclei in images, which necessitates determining whether each nucleus is located inside or outside the myotubes, leading to significant inter-observer variation. To address these challenges, this study proposes a three-stage process that integrates the strengths of pattern recognition and deep-learning to automatically calculate the fusion index.
View Article and Find Full Text PDFJ Med Syst
January 2025
Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), C/ Mare de Déu de Guadalupe, 2, Mataró, 08303, Barcelona, Spain.
Predicting health-related outcomes can help with proactive healthcare planning and resource management. This is especially important on the older population, an age group growing in the coming decades. Considering longitudinal rather than cross-sectional information from primary care electronic health records (EHRs) can contribute to more informed predictions.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, Belgium.
Fluorescence imaging has been widely used in fields like (pre)clinical imaging and other domains. With advancements in imaging technology and new fluorescent labels, fluorescence lifetime imaging is gradually gaining recognition. Our research department is developing the CAM, based on the Current-Assisted Photonic Sampler, to achieve real-time fluorescence lifetime imaging in the NIR (700-900 nm) region.
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