An intelligent health monitoring and diagnosis system based on the internet of things and fuzzy logic for cardiac arrhythmia COVID-19 patients

Computers in Biology and Medicine, Journal Year: 2023, Volume and Issue: 154, P. 106583 - 106583

Published: Jan. 25, 2023

Language: Английский

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Overview of Explainable Artificial Intelligence for Prognostic and Health Management of Industrial Assets Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Sensors, Journal Year: 2021, Volume and Issue: 21(23), P. 8020 - 8020

Published: Dec. 1, 2021

Surveys on explainable artificial intelligence (XAI) are related to biology, clinical trials, fintech management, medicine, neurorobotics, and psychology, among others. Prognostics health management (PHM) is the discipline that links studies of failure mechanisms system lifecycle management. There a need, which still absent, produce an analytical compilation PHM-XAI works. In this paper, we use preferred reporting items for systematic reviews meta-analyses (PRISMA) present state art XAI applied PHM industrial assets. This work provides overview trend in answers question accuracy versus explainability, considering extent human involvement, explanation assessment, uncertainty quantification topic. Research articles associated with subject, since 2015 2021, were selected from five databases following PRISMA methodology, several them sensors. The data extracted examined obtaining diverse findings synthesized as follows. First, while young, analysis indicates growing acceptance PHM. Second, offers dual advantages, where it assimilated tool execute tasks explain diagnostic anomaly detection activities, implying real need Third, review shows papers provide interesting results, suggesting performance unaffected by XAI. Fourth, role, evaluation metrics, areas requiring further attention community. Adequate assessment metrics cater needs requested. Finally, most case featured considered based data, some sensors, showing available blends solve real-world challenges, increasing confidence models’ adoption industry.

Language: Английский

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Machine learning and automatic ARIMA/Prophet models-based forecasting of COVID-19: methodology, evaluation, and case study in SAARC countries

Stochastic Environmental Research and Risk Assessment, Journal Year: 2022, Volume and Issue: 37(1), P. 345 - 359

Published: Oct. 5, 2022

Language: Английский

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Abnormality Detection and Failure Prediction Using Explainable Bayesian Deep Learning: Methodology and Case Study with Industrial Data

Mathematics, Journal Year: 2022, Volume and Issue: 10(4), P. 554 - 554

Published: Feb. 11, 2022

Mistrust, amplified by numerous artificial intelligence (AI) related incidents, is an issue that has caused the energy and industrial sectors to be amongst slowest adopter of AI methods. Central this black-box problem AI, which impedes investments fast becoming a legal hazard for users. Explainable (XAI) recent paradigm tackle such issue. Being backbone industry, prognostic health management (PHM) domain recently been introduced into XAI. However, many deficiencies, particularly lack explanation assessment methods uncertainty quantification, plague young domain. In present paper, we elaborate framework on explainable anomaly detection failure employing Bayesian deep learning model Shapley additive explanations (SHAP) generate local global from PHM tasks. An measure utilized as marker anomalies expands scope include model’s confidence. addition, used improve performance, aspect neglected handful studies PHM-XAI. The quality examined accuracy consistency properties. elaborated tested real-world gas turbine synthetic turbofan prediction data. Seven out eight were successfully identified. Additionally, outcome showed 19% improvement in statistical terms achieved highest score best published results topic.

Language: Английский

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Classifying COVID-19 based on amino acids encoding with machine learning algorithms

Chemometrics and Intelligent Laboratory Systems, Journal Year: 2022, Volume and Issue: 224, P. 104535 - 104535

Published: March 15, 2022

Language: Английский

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Multi-source data driven cryptocurrency price movement prediction and portfolio optimization

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 219, P. 119600 - 119600

Published: Jan. 25, 2023

Language: Английский

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On a Novel Dynamics of SEIR Epidemic Models with a Potential Application to COVID-19

Symmetry, Journal Year: 2022, Volume and Issue: 14(7), P. 1436 - 1436

Published: July 13, 2022

In this paper, we study a type of disease that unknowingly spreads for long time, but by default, only to minimal population. This is not usually fatal and often goes unnoticed. We propose derive novel epidemic mathematical model describe such disease, utilizing fractional differential system under the Atangana–Baleanu–Caputo derivative. deals with transmission between susceptible, exposed, infected, recovered classes. After formulating model, equilibrium points as well stability feasibility analyses are stated. Then, present results concerning existence positivity in solutions sensitivity analysis. Consequently, computational experiments conducted discussed via proper criteria. From our experimental results, find loss regain immunity result gain infections. Epidemic models can be linked symmetry asymmetry from distinct view. By using approach, much research may expected epidemiology other areas, particularly COVID-19, state how develops after being infected virus.

Language: Английский

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An IoT-fuzzy intelligent approach for holistic management of COVID-19 patients

Heliyon, Journal Year: 2023, Volume and Issue: 10(1), P. e22454 - e22454

Published: Nov. 20, 2023

In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription treatment patients with COVID-19. The main objective present study to develop integrated tool that combines IoT logic provide timely healthcare diagnosis within a smart framework. This tracks patients' health by utilizing Arduino microcontroller, small affordable computer reads data from various sensors, gather data. Once collected, are processed, analyzed, transmitted web page access via IoT-compatible Wi-Fi module. cases emergencies, such as abnormal blood pressure, cardiac issues, glucose levels, or temperature, immediate action can be taken monitor critical COVID-19 in isolation. employs recommend medical treatments patients. Sudden changes these conditions remotely reported through providers, relatives, friends. assists professionals making informed decisions based on patient's condition.

Language: Английский

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Interpretable Multi-Horizon Time Series Forecasting of Cryptocurrencies by Leverage Temporal Fusion Transformer

Heliyon, Journal Year: 2024, Volume and Issue: 10(22), P. e40142 - e40142

Published: Nov. 1, 2024

Language: Английский

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On Fuzzy and Crisp Solutions of a Novel Fractional Pandemic Model

Fractal and Fractional, Journal Year: 2023, Volume and Issue: 7(7), P. 528 - 528

Published: July 4, 2023

Understanding disease dynamics is crucial for accurately predicting and effectively managing epidemic outbreaks. Mathematical modeling serves as an essential tool in such understanding. This study introduces advanced susceptible, infected, recovered, dead (SIRD) model that uniquely considers the evolution of death parameter, alongside susceptibility infection states. accommodates varying environmental factors influencing susceptibility. Moreover, our SIRD fractional changes cases, which adds a novel dimension to traditional counts susceptible infected individuals. Given model’s complexity, we employ Laplace-Adomian decomposition method. The method allows us explore various scenarios, including non-fuzzy non-fractional, fractional, fuzzy cases. Our methodology enables determine equilibrium positions, compute basic reproduction number, confirm stability, provide computational simulations. offers insightful understanding into pandemic diseases underscores critical role mathematical plays devising effective public health strategies. ultimate goal improve management through precise predictions behavior spread.

Language: Английский

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