AIMC Topic: COVID-19
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Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.
PloS one
Mar 14, 2024
The COVID-19 pandemic has had a significant impact on both the United Arab Emirates (UAE) and Malaysia, emphasizing the importance of developing accurate and reliable forecasting mechanisms to guide public health responses and policies. In this study...
MIS-Net: A deep learning-based multi-class segmentation model for CT images.
PloS one
Mar 13, 2024
The accuracy of traditional CT image segmentation algorithms is hindered by issues such as low contrast and high noise in the images. While numerous scholars have introduced deep learning-based CT image segmentation algorithms, they still face challe...
Multi-modal deep learning methods for classification of chest diseases using different medical imaging and cough sounds.
PloS one
Mar 12, 2024
Chest disease refers to a wide range of conditions affecting the lungs, such as COVID-19, lung cancer (LC), consolidation lung (COL), and many more. When diagnosing chest disorders medical professionals may be thrown off by the overlapping symptoms (...
Binding Activity Classification of Anti-SARS-CoV-2 Molecules using Deep Learning Across Multiple Assays.
Balkan medical journal
Mar 11, 2024
BACKGROUND: The coronavirus disease-2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), has urgently necessitated effective therapeutic solutions, with a focus on rapidly identifying and classifying poten...
Evaluation of Effectiveness of Self-Supervised Learning in Chest X-Ray Imaging to Reduce Annotated Images.
Journal of imaging informatics in medicine
Mar 8, 2024
A significant challenge in machine learning-based medical image analysis is the scarcity of medical images. Obtaining a large number of labeled medical images is difficult because annotating medical images is a time-consuming process that requires sp...
Prognosis of COVID-19 severity using DERGA, a novel machine learning algorithm.
European journal of internal medicine
Mar 8, 2024
It is important to determine the risk for admission to the intensive care unit (ICU) in patients with COVID-19 presenting at the emergency department. Using artificial neural networks, we propose a new Data Ensemble Refinement Greedy Algorithm (DERGA...
Charting the future of patient care: A strategic leadership guide to harnessing the potential of artificial intelligence.
Healthcare management forum
Mar 5, 2024
Artificial Intelligence (AI) applications have the potential to revolutionize conventional healthcare practices, creating a more efficient and patient-centred approach with improved outcomes. This guide discuses eighteen AI-based applications in clin...
CODENET: A deep learning model for COVID-19 detection.
Computers in biology and medicine
Feb 29, 2024
Conventional COVID-19 testing methods have some flaws: they are expensive and time-consuming. Chest X-ray (CXR) diagnostic approaches can alleviate these flaws to some extent. However, there is no accurate and practical automatic diagnostic framework...
Empirical data drift detection experiments on real-world medical imaging data.
Nature communications
Feb 29, 2024
While it is common to monitor deployed clinical artificial intelligence (AI) models for performance degradation, it is less common for the input data to be monitored for data drift - systemic changes to input distributions. However, when real-time ev...
PulmoNet: a novel deep learning based pulmonary diseases detection model.
BMC medical imaging
Feb 28, 2024
Pulmonary diseases are various pathological conditions that affect respiratory tissues and organs, making the exchange of gas challenging for animals inhaling and exhaling. It varies from gentle and self-limiting such as the common cold and catarrh, ...
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