Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II)
This special issue introduces emerging intelligent healthcare technologies that incorporate big medical data, artificial intelligence, scientific computing, federated learning, bio-inspired computation, the Internet of Medical Things, security and privacy, semantic databases, etc. Health monitoring...
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| Format: | Article |
| Language: | English |
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Institute of Fundamental Technological Research Polish Academy of Sciences
2024-06-01
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| Series: | Computer Assisted Methods in Engineering and Science |
| Subjects: | |
| Online Access: | https://cames.ippt.pan.pl/index.php/cames/article/view/1692 |
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| author | Chinmay Chakraborty Sayonara Barbosa Lalit Garg |
| author_facet | Chinmay Chakraborty Sayonara Barbosa Lalit Garg |
| author_sort | Chinmay Chakraborty |
| collection | DOAJ |
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This special issue introduces emerging intelligent healthcare technologies that incorporate big medical data, artificial intelligence, scientific computing, federated learning, bio-inspired computation, the Internet of Medical Things, security and privacy, semantic databases, etc. Health monitoring and diagnosis for the target structure of interest are achieved through the interpretation of collected data. Advances in sensor technologies and data acquisition tools have led to a new era of big data, where massive amounts of medical data are collected by different sensors. This special issue offers valuable insights to researchers and engineers on designing intelligent bio-inspired Health 4.0 technologies and improving remote patient information delivery and care. By intelligently investigating and collecting large amounts of healthcare data (i.e., big data), sensors can enhance the decision-making process and help in early disease diagnosis. Hence, scalable machine learning, deep learning, and intelligent algorithms are needed to develop more interoperable solutions and make effective decisions in emerging sensor technologies. Optimization algorithms can be applied to acquire sensor data from multiple sources for fast and accurate health monitoring. In this special issue, seven manuscripts are published. The papers are directly or indirectly related to advanced clustering, imaging, and computing for bio-signal acquisition systems with intelligent computing.
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| format | Article |
| id | doaj-art-02a408ff4d8e496ca1f8ba3c1e8bcddd |
| institution | Kabale University |
| issn | 2299-3649 2956-5839 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Institute of Fundamental Technological Research Polish Academy of Sciences |
| record_format | Article |
| series | Computer Assisted Methods in Engineering and Science |
| spelling | doaj-art-02a408ff4d8e496ca1f8ba3c1e8bcddd2025-08-20T03:28:58ZengInstitute of Fundamental Technological Research Polish Academy of SciencesComputer Assisted Methods in Engineering and Science2299-36492956-58392024-06-01312Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II)Chinmay Chakraborty0Sayonara Barbosa1Lalit Garg2Birla Institute of Technology, Mesra, JharkhandFederal University of Santa Catarina, FlorianópolisUniversity of Malta, Msida This special issue introduces emerging intelligent healthcare technologies that incorporate big medical data, artificial intelligence, scientific computing, federated learning, bio-inspired computation, the Internet of Medical Things, security and privacy, semantic databases, etc. Health monitoring and diagnosis for the target structure of interest are achieved through the interpretation of collected data. Advances in sensor technologies and data acquisition tools have led to a new era of big data, where massive amounts of medical data are collected by different sensors. This special issue offers valuable insights to researchers and engineers on designing intelligent bio-inspired Health 4.0 technologies and improving remote patient information delivery and care. By intelligently investigating and collecting large amounts of healthcare data (i.e., big data), sensors can enhance the decision-making process and help in early disease diagnosis. Hence, scalable machine learning, deep learning, and intelligent algorithms are needed to develop more interoperable solutions and make effective decisions in emerging sensor technologies. Optimization algorithms can be applied to acquire sensor data from multiple sources for fast and accurate health monitoring. In this special issue, seven manuscripts are published. The papers are directly or indirectly related to advanced clustering, imaging, and computing for bio-signal acquisition systems with intelligent computing. https://cames.ippt.pan.pl/index.php/cames/article/view/1692Smart Healthcareintelligent healthcare technologiesbig medical dataartificial intelligencescientific computingbio-inspired computation |
| spellingShingle | Chinmay Chakraborty Sayonara Barbosa Lalit Garg Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II) Computer Assisted Methods in Engineering and Science Smart Healthcare intelligent healthcare technologies big medical data artificial intelligence scientific computing bio-inspired computation |
| title | Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II) |
| title_full | Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II) |
| title_fullStr | Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II) |
| title_full_unstemmed | Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II) |
| title_short | Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II) |
| title_sort | preface to special issue on scientific computing and learning analytics for smart healthcare systems part ii |
| topic | Smart Healthcare intelligent healthcare technologies big medical data artificial intelligence scientific computing bio-inspired computation |
| url | https://cames.ippt.pan.pl/index.php/cames/article/view/1692 |
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