Examination of the Effects of Long-term COVID-19 Impacts on Patients with Neurological Disabilities Using a Neuromachine Learning Model

Vaniprabha, A; Logeshwaran, J; Kiruthiga, T; Shah, Krishna Bikram

doi:10.54646/bijnn.003

Cited by 76 publications

(5 citation statements)

References 21 publications

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“…Vaniprabha et al [168] investigated the neurological consequences of long COVID on patients using a Neuromachine Learning Model. The study's findings suggest that traces of the virus may persist in the bodies of individuals with neurological disabilities even after two weeks, despite negative test results.…”

Section: Overview Of Current Approaches To Managing Long Covidmentioning

confidence: 99%

Are the Comorbidities Constitute an Intrinsic Factor for Long COVID?

Ashmawy,

Hammouda,

El-Maradny

et al. 2024

Preprint

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Long COVID, a name often given to the persistent symptoms following acute SARS-CoV-2 infection, poses a multifaceted challenge for health. This review explores the intrinsic relationship between comorbidities and autoimmune responses in shaping the trajectory of long COVID. Autoantibodies have emerged as significant players in COVID-19 pathophysiology, with implications for disease severity and progression. Studies show immune dysregulation persisting months after infection, marked by activated innate immune cells and high cytokine levels. The presence of autoantibodies against various autoantigens suggests their potential as comorbid factors in long COVID. Additionally, the formation of immune complexes may lead to severe disease progression, highlighting the urgency for early detection and intervention. Furthermore, long COVID is highly linked to cardiovascular complications and neurological symptoms, posing challenges in diagnosis and management. Multidisciplinary approaches, including vaccination, tailored rehabilitation, and pharmacological interventions, are used for mitigating long COVID's burden. However, numerous challenges persist, from evolving diagnostic criteria to addressing the psychosocial impact and predicting disease outcomes. Leveraging AI-based applications holds promise in enhancing patient management and improving our understanding of long COVID. As research continues to unfold, unravelling the complexities of long COVID remains paramount for effective intervention and patient care.

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Section: Overview Of Current Approaches To Managing Long Covidmentioning

confidence: 99%

Are the Comorbidities Constitute an Intrinsic Factor for Long COVID?

Ashmawy,

Hammouda,

El-Maradny

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The management server instructs the agent program installed on the client computer to start backing up data according to the selected policy in accordance with the schedule or according to the operator's command (48). The agent program collects and transfers the data to be backed up to the copy server specified by the management server (49). The mechanism of action of "snapshots" is different and can be implemented both in software on a production server and in hardware within the array (50).…”

Section: Related Workmentioning

confidence: 99%

A secured database monitoring method to improve databackup and recovery operations in cloud computing

Ramesh,

Logeshwaran,

Aravindarajan

2023

BIJSCIT

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In general, the company sometimes uses unregistered functions in database, which significantly improvesperformance, but does not leave the possibility of recovery except for backup. That is, actions must be performedimmediately after passing the session. A queue problem is likely to cause data loss and downtime of about aweek. In modern conditions, this can lead to the bankruptcy of the company. It can be seen that backup systemshave been installed and configured, but despite this, they have not succeeded in restoring within the time framespecified in the SLA. In this study, a secured database monitoring method was proposed to improve data backupand recovery operations in cloud computing. In this proposed method, the backup speed is directly proportionalto the amount of data, while having at least 30% annual data growth. In 3–4 years, the data at least doubled, butfor some companies, this number is even higher, while the backup speed does not change. Those terms and thoseSLAs that were relevant 3–4 years ago now need to be at least doubled. At the same time, business requirementsfor data recovery (recovery point objective/recovery time objective) continue to grow.

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“…A fuzzy scheme hierarchical proposed technique is Fuzzy Logic-Based Energy Efficient Clustering Hierarchy (FLECH) (18). Throughout this technique, "remaining energy," "focusing rate," and "length to the BS" are used to select the cluster.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dust

Rajesh¹,

Rajanna²

2020

BIJSCIT

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Sensor nodes in smart dust are used to track and identify data that is being transferred to a sink. The accessibility of node energy poses a significant challenge for smart dust and may have an impact on the long-term viability of the network. As a result, constructing smart dust must take into account the need for algorithms and techniques that enable the most use of scarce resources, especially energy resources. For instance, routing algorithms are distinctive algorithms because they have a clear and direct connection with network longevity and energy. The offered routing techniques use clustering each round and single-hop data delivery to the sink. A Fuzzy Clustering and Energy Resourceful Routing Protocol (FCER2P) that reduces smart dust energy consumption and lengthens lifespan of the network is proposed in this research. Using a specified threshold, FCER2P proposes a new cluster-based fuzzy routing mechanism that can make use of clustering and multiple hop routing capabilities simultaneously. This research is innovative in that it adjusts multi-hop connectivity by anticipating the optimum intermediate node for aggregating and the sink, eliminates clustering each round while taking a fixed threshold into account, and eliminates clustering per round altogether. When choosing the intermediary node to employ, some fuzzy parameters, including residual energy, the number of neighbors, and the distance to the sink, are taken into account.

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Examination of the Effects of Long-term COVID-19 Impacts on Patients with Neurological Disabilities Using a Neuromachine Learning Model

Cited by 76 publications

References 21 publications

Are the Comorbidities Constitute an Intrinsic Factor for Long COVID?

Are the Comorbidities Constitute an Intrinsic Factor for Long COVID?

A secured database monitoring method to improve databackup and recovery operations in cloud computing

Fuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dust

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