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An Early Warning Tool for Predicting Mortality Risk of COVID-19 Patients Using Machine Learning
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Springer
, 2021 , Article)
COVID-19 pandemic has created an extreme pressure on the global healthcare services. Fast, reliable, and early clinical assessment of the severity of the disease can help in allocating and prioritizing resources to reduce ...
Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
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Elsevier
, 2021 , Article)
Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA1c (A1C). It is a biomarker for diagnosis of diabetes and prediabetes and of medium-term glycemic control in patients with established ...
Fusion of Machine Learning and Privacy Preserving for Secure Facial Expression Recognition
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Hindawi
, 2021 , Article)
The interest in Facial Expression Recognition (FER) is increasing day by day due to its practical and potential applications, such as human physiological interaction diagnosis and mental disease detection. This area has ...
A review of smart sensors coupled with Internet of Things and Artificial Intelligence approach for heart failure monitoring
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Springer Nature
, 2021 , Article)
Over the last decade, there has been a huge demand for health care technologies such as sensors-based prediction using digital health. With the continuous rise in the human population, these technologies showed to be ...
Forecasting the impact of environmental stresses on the frequent waves of COVID19
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Springer
, 2021 , Article)
A novel approach to link the environmental stresses with the COVID-19 cases is adopted during this research. The time-dependent data are extracted from the online repositories that are freely available for knowledge and ...
Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Electroencephalography (EEG) based biometric systems are gaining attention for their anti-spoofing capability but lack accuracy due to signal variability at different psychological and physiological conditions. On the other ...
Predicting carbonate formation permeability using machine learning
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Elsevier B.V.
, 2020 , Article)
It is imperative to characterize the formation permeability to simulate the flow behavior at subsurface conditions. An accurate characterization at the core scale is possible when large samples are available, but often ...
Real-time throughput prediction for cognitive Wi-Fi networks
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Academic Press
, 2020 , Article)
Wi-Fi as a wireless networking technology has become a widely acceptable commonplace. Over the course of time, the applications landscape of Wi-Fi networks is growing tremendously. The proliferation of new services is ...
MACHINE LEARNING APPLICATION FOR OPTIMIZING ASYMMETRICAL REDUCTION OF ACETOPHENONE EMPLOYING COMPLETE CELL OF LACTOBACILLUS SENMAIZUKE AS AN ENVIRONMENTALLY FRIENDLY APPROACH
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Prof. Hysen Mankolli, IJEES Electronic Journal Publication
, 2020 , Article)
Recently, optimization of the bioreduction reactions by optimization methodologies has gained special interest as these reactions are affected by several extrinsic factors that should be optimized for higher yields. An ...
An adaptive network coding scheme for multipath transmission in cellular-based vehicular networks
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MDPI AG
, 2020 , Article)
With the emergence of vehicular Internet-of-Things (IoT) applications, it is a significant challenge for vehicular IoT systems to obtain higher throughput in vehicle-to-cloud multipath transmission. Network Coding (NC) has ...