A Blockchain-Based Privacy-Preserving Healthcare Data Sharing Scheme for Incremental Updates
L Wang, X Liu, W Shao, C Guan, Q Huang, S Xu… - Symmetry, 2024 - mdpi.com
With the rapid development of artificial intelligence (AI) in the healthcare industry, the
sharing of personal healthcare data plays an essential role in advancing medical AI …
sharing of personal healthcare data plays an essential role in advancing medical AI …
[HTML][HTML] Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis
C Wang, S Liu, Y Tang, H Yang, J Liu - Journal of Medical Internet …, 2023 - jmir.org
Background Deep learning (DL) prediction models hold great promise in the triage of COVID-
19. Objective We aimed to evaluate the diagnostic test accuracy of DL prediction models for …
19. Objective We aimed to evaluate the diagnostic test accuracy of DL prediction models for …
Discovery of raffinose sulfate as a potential SARS CoV-2 inhibitor via blocking its binding with angiotensin converting enzyme 2
The present study aimed to characterize the possible binding sites on the SARS CoV-2 RBD-
ACE2 complex and to highlight sulfated oligosaccharides as potential anti-SARS CoV-2 via …
ACE2 complex and to highlight sulfated oligosaccharides as potential anti-SARS CoV-2 via …
Synergizing AI, IoT, and Blockchain for Diagnosing Pandemic Diseases in Smart Cities: Challenges and Opportunities
I Alrashdi, A Alqazzaz - Sustainable Machine Intelligence …, 2024 - sciencesforce.com
The advent of smart cities has paved the way for transformative advancements in healthcare,
particularly in the domain of disease diagnosis. In the wake of the COVID-19 pandemic …
particularly in the domain of disease diagnosis. In the wake of the COVID-19 pandemic …
Prognosis prediction in covid-19 patients through deep feature space reasoning
The COVID-19 pandemic has presented a unique challenge for physicians worldwide, as
they grapple with limited data and uncertainty in diagnosing and predicting disease …
they grapple with limited data and uncertainty in diagnosing and predicting disease …
Inverse design of electromagnetically induced transparency (EIT) metasurface based on deep convolutional generative adversarial network
L Zhu, C Zhang, L Dong, MX Rong, JY Gong… - Physica …, 2023 - iopscience.iop.org
With the increasing complexity of electromagnetically induced transparency (EIT)
metasurface structure and the limitations of traditional optimization methods, there is an …
metasurface structure and the limitations of traditional optimization methods, there is an …
[HTML][HTML] Improving the quality evaluation process of machine learning algorithms applied to landslide time series analysis
Abstract The introduction of Machine Learning (ML) in the geotechnical community has led
to numerous applications for monitoring data elaboration. These techniques demonstrate …
to numerous applications for monitoring data elaboration. These techniques demonstrate …
Scoping Review of Deep Learning Techniques for Diagnosis, Drug Discovery, and Vaccine Development in Leishmaniasis
Leishmania, a single‐cell parasite prevalent in tropical and subtropical regions worldwide,
can cause varying degrees of leishmaniasis, ranging from self‐limiting skin lesions to …
can cause varying degrees of leishmaniasis, ranging from self‐limiting skin lesions to …
Medical image segmentation method based on multi‐scale feature and U‐net network
J Wang - Internet Technology Letters, 2023 - Wiley Online Library
In medical image segmentation (MIS), better segmentation results can be obtained by
training the deeper neural network. However, directly building too deep network will cause …
training the deeper neural network. However, directly building too deep network will cause …
Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine
Liquid chromatography–mass spectrometry (LC–MS)-based untargeted metabolomics
provides systematic profiling of metabolic. Yet, its applications in precision medicine …
provides systematic profiling of metabolic. Yet, its applications in precision medicine …