The recent COVID-19 outbreak highlighted the requirement for a more sophisticated healthcare system and real-time data analytics in the pandemic mitigation process. Moreover, real-time data plays a crucial role in the detection and alerting process. Combining smart healthcare systems with accurate real-time information about medical service availability, vaccination, and how the pandemic is spreading can directly affect the quality of life and economy. The existing architecture models are become inadequate in handling the pandemic mitigation process using real-time data. The present models are server-centric and controlled by a single party, where the management of confidentiality, integrity, and availability (CIA) of data is doubtful. Therefore, a decentralised user-centric model is necessary, where the CIA of user data is assured. In this paper, we have suggested a decentralized blockchain-based pandemic detection and assistance system (iBlock). The iBlock uses robust technologies like hybrid computing and IPFS to support system functionality. A pseudo-anonymous personal identity is introduced using H-PCS and cryptography for anonymous data sharing. The distributed data management module guarantees data CIA, security, and privacy using cryptography mechanisms. Furthermore, it delivers useful intelligent information in the form of suggestions and alerts to assist the users. Finally, the iBlock reduces stress on healthcare infrastructure and workers by providing accurate predictions and early warnings using AI/ML.
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http://dx.doi.org/10.1007/s11265-021-01704-9 | DOI Listing |
Gastroenterology
March 2025
APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, Ireland.
Inflammatory bowel disease (IBD) is marked by significant clinical heterogeneity, posing challenges for accurate diagnosis and personalized treatment strategies. Conventional approaches, such as endoscopy and histology, often fail to adequately and accurately predict medium and long-term outcomes, leading to suboptimal patient management. Artificial intelligence (AI) is emerging as a transformative force enabling standardized, accurate, and timely disease assessment and outcome prediction, including therapeutic response.
View Article and Find Full Text PDFEur J Dent
March 2025
Department of Periodontology, Faculty of Dentistry, Universitas Indonesia, Jakarta, Indonesia.
Objective: Regenerative periodontal surgical approaches require scaffolds in a form that can fill narrow and irregular defects. Each scaffold must be specially designed to conform to the shape of the specific defect. The aim of this study was to fabricate nanohydroxyapatite chitosan-gelatin (nHA/KG) pastes with different composition percentages and to analyze the differences in physical, chemical, and biological characteristics in response to periodontal tissue regeneration .
View Article and Find Full Text PDFUltramicroscopy
March 2025
Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Forschungszentrum Jülich, 52425 Jülich, Germany.
Collecting and averaging large datasets is a common practice in transmission electron microscopy to improve the signal-to-noise ratio. Averaging data in off-axis electron holography requires automated tools capable of correcting both the drift of the interference fringes and the drift of the specimen. This can be achieved either off-line, by post-processing hologram series, or on-line, through real-time microscope control.
View Article and Find Full Text PDFMed Image Anal
February 2025
School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK.
Accurate judgment and identification of polyp size is crucial in endoscopic diagnosis. However, the indistinct boundaries of polyps lead to missegmentation and missed cancer diagnoses. In this paper, a prompt-based polyp segmentation method (PPSM) is proposed to assist in early-stage cancer diagnosis during endoscopy.
View Article and Find Full Text PDFJ Neural Eng
March 2025
Electrical and Computer Engineering, University of Tehran College of Engineering, North Kargar Street, Tehran, Tehran, Tehran, 1439957131, Iran (the Islamic Republic of).
Despite remarkable advances in EMG-based hand motor decoding, developing a practical and reliable decoder for robotic prosthetic hands remains unsolved. This study highlights inter-individual, inter-session, and intra-session variabilities of EMG signals as practical challenges and introduces a novel personalized and adaptive motor decoding framework, designed to mitigate their impact and improve hand motor decoding. A dataset was collected from twelve participants (8 male, 4 female), incorporating EMG signals from three forearm muscles during 20 repetitions of 9 distinct hand motions.
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