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54 results for “Healthcare Systems”
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Research ArticleOpen accessIn the abstractTowards a Human-Like AGI Architecture: General Intelligence Framework (GIF)Jiran Kurian Puliyanmakkal, Rohini VArtificial Intelligence (AI) has achieved significant breakthroughs but remains limited by its specialization and inability to generalize across domains, unlike human cognition. Current models such as Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) excel at specific tasks but struggle with real-time adaptability and cross-domain generalization. This paper introduces the General Intelligence Framework (GIF), an approach designed to … …Journal of Computer Science, Vol. 21, Issue 7 · 13 Jul 2025 · 4,435 accessesView PDFCite
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Analysis of Smote and CSSF Techniques for Diabetes Classification Using Imbalanced DataBashar Hamad Aubaidan, Rabiah Abdul Kadir, Mohamad Taha IjabDiabetes, a prevalent chronic metabolic disorder, poses a significant burden on healthcare systems worldwide. Accurate and timely diagnosis is crucial for effective management and complication prevention. Machine learning presents a promising solution but often faces challenges due to class imbalance within datasets, particularly the underrepresentation of diabetic cases. To address this issue, we introduce Cluster-based Synthetic Sample Filtering (CSSF), a … …Journal of Computer Science, Vol. 20, Issue 9 · 22 Jul 2024 · 4,998 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart Patient Consent Management Model for Health Information Exchange Based on Blockchain TechnologyK. R. Rohini, P. S. Rajakumar, S. GeethaInnovation for Electronic Medical Records (EMRs) has been hindered by years of excessive regulation and inefficient bureaucracy. As data science and personalization encourage individuals to take an active role in their healthcare and regain control of their own medical records, there is an urgent need for new approaches. The ability to exchange electronic health records is fundamental in contemporary healthcare … …Journal of Computer Science, Vol. 20, Issue 7 · 17 Apr 2024 · 7,343 accessesView PDFCite
Review ArticleOpen accessIn the abstractChallenges of Breast Cancer Detection Based on Histopathology ImagesAlaa Mohamed Youssef, Aliaa Abdel-Haleim Abdel-Razik Youssif, Wessam El BehaidyArtificial Intelligence (AI) is rapidly evolving every day to become increasingly potent and dependable. AI systems are becoming more sophisticated and are being utilized across various domains with the goal of enhancing human existence. Within the healthcare system, artificial intelligence finds application in handling and documenting large volumes of medical data, conducting analyses of healthcare systems, advancing pharmaceutical development, and … …Journal of Computer Science, Vol. 20, Issue 7 · 17 Apr 2024 · 4,942 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Holistic Approach to Security, Availability and Reliability in Fog ComputingAbdulrahman Alshehri, Hazzaa Alshareef, Samah Alhazmi et al.Abdulkareem, K. H., Mohammed, M. A., Gunasekaran, S. S., Al-Mhiqani, M. N., Mutlag, A. A., Mostafa, S. A., Ali, N. S., & Ibrahim, D. A. (2019). A Review of Fog Computing and Machine Learning: Concepts, Applications, Challenges, and Open Issues. IEEE Access, 7, 153123–153140. https://doi.org/10.1109/access.2019.2947542 Alrawais, A., Alhothaily, A., Hu, C., & Cheng, X. (2017). Fog Computing for the Internet … …Journal of Computer Science, Vol. 20, Issue 6 · 20 Mar 2024 · 6,372 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Prediction Studies Using Wearable Sensors and Machine LearningDivya Sharma, Usha ChauhanNowadays, Human Activity Recognition (HAR) systems have become so demanding that they find applications in the field of assisted living systems, elderly healthcare systems, smart homes, healthcare monitoring applications, surveillance systems, etc. Due to its increasing demand in computer science; machine learning and deep learning have brought a paradigm shift in the area of sensor-based recognition systems. Providing accurate information … …Journal of Computer Science, Vol. 20, Issue 4 · 14 Feb 2024 · 7,201 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Use of 3D Scanning and 3D Color Printing Technologies for the Study and Documentation of Late Bronze Age Pottery from East-Central GreeceAntreas Kantaros, Maria I. Papageorgiou, Konstantinos Brachos et al.Antreas, K., & Piromalis, D. (2021). Employing a Low-Cost Desktop 3D Printer: Challenges, and How to Overcome Them by Tuning Key Process Parameters. International Journal of Mechanics and Applications, 10(1), 11–19. https://doi.org/10.5923/j.mechanics.20211001.02 Bachi, V., Fresa, A., Pierotti, C., & Prandoni, C. (2014). The Digitization Age: Mass Culture Is Quality Culture. Challenges for Cultural Heritage and Society (Vol. 8740, pp. 786–801). … …Journal of Mechatronics and Robotics, Vol. 8, Issue 1 · 24 May 2024 · 5,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnxiety-Focused Classification Using Smartphone-Based Gait Analysis and Deep Learning ModelsMinchan Kang, Gou-Sung Degbey, Hyunhwa Lee et al.Mood disorders, such as anxiety, significantly impact individual well-being and present challenges to healthcare systems globally. Traditional screening methods, including self-administered symptom questionnaires, provide valuable insights into symptoms but may miss dynamic fluctuations. This study explores the potential of smartphone inertial sensors and deep learning models for anxiety risk classification. Using gait data from 36 participants, collected via smartphone accelerometers … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 821 accessesView PDFCite