Centralized and Automated Healthcare Systems : A Essential Smart Application Post Covid-19

H, Rama Moorthy; Udupa, Sahana; Bhagavath, Samanvitha A; Shreesha,; Rao, Varun

doi:10.1109/iciss49785.2020.9316103

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…The study in [31] represents the characteristics, ap-plications and benefits of cloud computing and elaborates the improvement essential for cloud during COVID-19. The cloud computing helps the countries in handling the COVID 19, in commercial, educational, economic and health sectors.…”

Section: Cloud Computingmentioning

confidence: 99%

Post-Covid Remote Patient Monitoring using Medical Internet of Things and Machine Learning Analytics

Rahman

Parveen

Sofi

et al. 2023

SCPE

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The Covid-19 pandemic disturbed the smooth functioning of healthcare services throughout the world. New practices such as masking, social distancing and so on were followed to prevent the spread. Further, the severity of the problem increases for the elderly people and people having co-morbidities as proper medical care was not possible and as a result many deaths were recorded. Even for those patients who recovered from Covid could not get proper health monitoring in the Post-Covid phase as a result many deaths and severity in health conditions were reported after the Covid recovery i.e., the Post-Covid era. Technical interventions like the Internet of Things (IoT) based remote patient monitoring using Medical Internet of Things (M-IoT) wearables is one of the solutions that could help in the Post-Covid scenarios. The paper discusses a proposed framework where in a variety of IoT sensing devices along with ML algorithms are used for patient monitoring by utilizing aggregated data acquired from the registered Post-Covid patients. Thus, by using M-IoT along with Machine Learning (ML) approaches could help us in monitoring Post-Covid patients with co-morbidities for and immediate medical help.

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Section: Cloud Computingmentioning

confidence: 99%

Post-Covid Remote Patient Monitoring using Medical Internet of Things and Machine Learning Analytics

Rahman

Parveen

Sofi

et al. 2023

SCPE

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Machine Learning-Based Emerging Technologies in the Post Pandemic Scenario

Priya

Abirami²,

Desai³

2022

Artificial Intelligence and Machine Learning Methods in COVID-19 and Related Health Diseases

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An ontology-based approach to designing a NoSQL database for semi-structured and unstructured health data

Sen

Mukherjee

2023

Cluster Comput

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With the advent of ICT-based healthcare applications, various formats of health data are generated every day in huge volume. Such data, consisting of unstructured, semi-structured and structured data, has every characteristic of Big data. NoSQL databases are generally preferred for storing such type of health data with the objective of improving query performance. However, for efficient retrieval and processing of Big Health Data and for resource optimization, suitable data models and design of the NoSQL databases are important requirements. Unlike relational databases, no standard methods or tools exist for NoSQL database design. In this work, we adopt an ontology-based schema design approach. We propose that an ontology, which captures the domain knowledge, be used for developing a health data model. An ontology for primary healthcare is described in this paper. We also propose an algorithm for designing the schema of a NoSQL database, keeping in mind the characteristics of the target NoSQL store, using a related ontology, a sample query set, some statistical information of the queries, and performance requirements of the query set. The ontology proposed by us for primary healthcare domain and the above mentioned algorithm along with a set of queries are used for generating a schema targeting MongoDB datastore. The performance of the proposed design is compared with a relational model developed for the same primary healthcare data and the effectiveness of our proposed approach is demonstrated. The entire experiment has been carried out on MongoDB cloud platform.

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Centralized and Automated Healthcare Systems : A Essential Smart Application Post Covid-19

Cited by 5 publications

References 13 publications

Post-Covid Remote Patient Monitoring using Medical Internet of Things and Machine Learning Analytics

Post-Covid Remote Patient Monitoring using Medical Internet of Things and Machine Learning Analytics

Machine Learning-Based Emerging Technologies in the Post Pandemic Scenario

An ontology-based approach to designing a NoSQL database for semi-structured and unstructured health data

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