Designing Adaptive Mechanism for COVID-19 and Exacerbation in Cases of COPD Patients Using Machine Learning Approaches
Konan-Marcelin Kouamé,
Hamid Mcheick
Issue:
Volume 10, Issue 5, October 2021
Pages:
81-97
Received:
24 September 2021
Accepted:
21 October 2021
Published:
30 October 2021
Abstract: The technology of machine learning has been widely applied in several domains and complex medical problems, specifically in chronic obstructive pulmonary disease (COPD). Researchers in the field of respiratory diseases confirm that people who suffer from COPD have high risks when exposed to COVID-19. The most common oncoming COPD exacerbations and COPD symptoms of COVID-19 are congruent. The distinction between COPD exacerbations and COVID-19 with COPD is nearly impossible without testing. This paper proposes a new powerful model for classifying COPD patients with exacerbations and those with COVID-19 using machine learning and deep learning algorithms. The major contribution of this research is the dynamic classification process based on the patient context that can help detect exacerbations or COVID-19 per period. Indeed, Five Machine Learning algorithms are trained, tested and a performant classification model is identified. This prediction model is then associated with a dynamic COPD patient context for monitoring the patient's health status. This model based on the dynamic adaptation mechanism combined with a classification contributes to identifying dynamically COPD exacerbations and COVID-19 symptoms for COPD patients. Indeed, periodically, data on a new patient is injected into the prediction model. At the output of the model, the patient is either classified in the exacerbation category, or classified in the COVID-19 category, or no category. By period. A dynamic dashboard of classified patients is available to help medical staff take appropriate decisions. This approach helps to follow the evolution of COPD patient comorbidities (exacerbation, COVID-19). Finally, classification would allow healthcare stakeholders to provide healthcare service according to the patient’s status. The methodology of research consists of designing and implementing a dynamic model for classifying COPD patients. Since early intervention is associated with improved prognosis, with our solution, healthcare staff can identify COPD patients who are most at risk of developing exacerbation or COVID-19. Consequently, upon admission, this will ensure that these patients receive appropriate care as soon as possible.
Abstract: The technology of machine learning has been widely applied in several domains and complex medical problems, specifically in chronic obstructive pulmonary disease (COPD). Researchers in the field of respiratory diseases confirm that people who suffer from COPD have high risks when exposed to COVID-19. The most common oncoming COPD exacerbations and ...
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Construction of Blockchain Product Technology Evaluation Index System
Issue:
Volume 10, Issue 5, October 2021
Pages:
98-103
Received:
18 October 2021
Accepted:
9 November 2021
Published:
12 November 2021
Abstract: Blockchain products are more and more widely used. How to reasonably evaluate blockchain products has become a hot issue. The main work of this paper is to establish a set of general evaluation indicators for blockchain products, and analyze the needs of future software systems. Firstly, the paper analyzes the common five-tier architecture adopted by the current blockchain system, namely data layer, network layer, consensus layer, smart contract layer and application layer, and expounds the hierarchical characteristics and technical contents of each layer in detail; Then on this basis, a set of general evaluation indicators is proposed for the current common blockchain products, in which the evaluation indicators can be divided into six items: distributed ledger evaluation indicators, public key password evaluation indicators, point-to-point network technology evaluation indicators, consensus mechanism evaluation indicators, intelligent contract mechanism evaluation indicators and upper layer application evaluation indicators. The establishment of indicators can comprehensively evaluate the availability, security and system performance of blockchain products. Finally, based on the evaluation index, the functional and non functional analysis of the blockchain product evaluation system is carried out, which lays a good foundation for the realization of software in the future. The design of evaluation indicators and the functional analysis of the evaluation system will promote the standardization of blockchain products.
Abstract: Blockchain products are more and more widely used. How to reasonably evaluate blockchain products has become a hot issue. The main work of this paper is to establish a set of general evaluation indicators for blockchain products, and analyze the needs of future software systems. Firstly, the paper analyzes the common five-tier architecture adopted ...
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Machine Learning Translation of English into Igbo Language: A Review
Orji Ifeoma Maryann,
Sylvanus Okwudili Anigbogu,
Ekwelaro Oluchukwu Uzoamaka,
Asogwa Doris Chinedu
Issue:
Volume 10, Issue 5, October 2021
Pages:
104-108
Received:
3 October 2021
Accepted:
1 November 2021
Published:
12 November 2021
Abstract: Machine learning is the machine translation used in language. A lot of people have been using it and it’s working extremely well for them. It works without delay and is getting better as day passes. Of course, this advancement will change the way the modern world operates because language barriers have been an essential impediment to international commerce since time immemorial. Language is tagged with cultural disposition of people’s ways of life. Without language there will be no existence of the world and the people living within it. The necessity of translation comes into existence because of the migration of people from one country to another. Language translation is the key technology for the in-coming generation of IT and every digital device uses it and is dependence on it. The objective of the paper is to review a machine learning translation of English to Igbo language. The major concept reviewed was machine learning in term of dealing with language translation. Machine learning is a wide and interesting field in computer science. This has been tagged as an awesome professional area for research in demands for translation of languages. Many researchers preferred using supervised learning in doing language translation while few researchers used unsupervised learning in doing language translation.
Abstract: Machine learning is the machine translation used in language. A lot of people have been using it and it’s working extremely well for them. It works without delay and is getting better as day passes. Of course, this advancement will change the way the modern world operates because language barriers have been an essential impediment to international ...
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