An AI healthcare ecosystem framework for Covid-19 detection and forecasting using CronaSona

Medical & Biological Engineering & Computing, Journal Year: 2024, Volume and Issue: 62(7), P. 1959 - 1979

Published: March 13, 2024

Abstract The primary purpose of this paper is to establish a healthcare ecosystem framework for COVID-19, CronaSona. Unlike some studies that focus solely on detection or forecasting, CronaSona aims provide holistic solution, managing data and/or knowledge, incorporating detection, expert advice, treatment recommendations, real-time tracking, and finally visualizing results. innovation lies in creating comprehensive an application not only aids COVID-19 diagnosis but also addresses broader health challenges. main objective introduce novel designed simplify the development construction applications by standardizing essential components required focused addressing diseases. includes two parts, which are stakeholders shared components, four subsystems: (1) management information subsystem, (2) (3) forecasting (4) mobile tracker subsystem. In proposed framework, app. was built try put virus under control. It reactive all users, especially patients doctors. reliable diagnostic tool using deep learning techniques, accelerating referral processes, focuses transmission COVID-19. subsystem monitoring potential carriers minimizing spread. compete with other help people face virus. Upon receiving developed validate test framework’s functionalities. aim application, app., develop techniques avoid increasing spread disease as much possible accelerate detecting features from their chest X-ray images. By CronaSona, human saved stress reduced knowing everything about performs highest accuracy, F1-score, precision, consecutive values 97%, 97.6%, 96.6%. Graphical

Language: Английский

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RETRACTED: Bi-directional ConvLSTM residual U-Net retinal vessel segmentation algorithm with improved focal loss function

Journal of Intelligent & Fuzzy Systems, Journal Year: 2024, Volume and Issue: 46(4), P. 10167 - 10186

Published: April 2, 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.

Language: Английский

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Deep-CNWO: a deep-chaotic nature whale optimization algorithm for early prediction of blood pressure disorder in smart healthcare settings

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(24), P. 15117 - 15136

Published: May 13, 2024

Language: Английский

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Enhancing IoT Networking Through Predictive Big Data Processing

Published: March 15, 2024

the net of things (IoT) promises to revolutionize way humans interact with their surroundings. Notwithstanding this promise, deployment IoT networks is hindered by using several challenges, particularly related communication, scalability, and electricity performance. This paper proposes a technique address those demanding situations through predictive big statistics processing blended use new network technology. In particular, prediction fashions, system studying, analytics algorithms will permit investigate past present facts in order forecast destiny traits. Additionally, latest existing technologies, which include extremely-low strength mesh networks, 5G, electricity-conscious routing protocols help improve overall performance networks. conclusion, gives method decorate characteristic as more effective, efficient, reliable communique for all devices.

Language: Английский

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Survey of the loss function in classification models: Comparative study in healthcare and medicine

Multimedia Tools and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: June 5, 2024

Language: Английский

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