Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning

Journal of Business Research, Journal Year: 2022, Volume and Issue: 156, P. 113480 - 113480

Published: Dec. 2, 2022

Language: Английский

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Artificial Intelligence-Based Data-Driven Strategy to Accelerate Research, Development, and Clinical Trials of COVID Vaccine

BioMed Research International, Journal Year: 2022, Volume and Issue: 2022, P. 1 - 16

Published: July 6, 2022

The global COVID-19 (coronavirus disease 2019) pandemic, which was caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a significant loss of human life around world. SARS-CoV-2 problems to medical systems and healthcare facilities due its unexpected expansion. Despite all efforts, developing effective treatments, diagnostic techniques, vaccinations for this unique virus is top priority takes long time. However, foremost step vaccine development identify possible antigens vaccine. traditional method time taking, but after breakthrough technology reverse vaccinology (RV) introduced 2000, it drastically lowers needed detect ranging from 5–15 years 1–2 years. different RV tools work based on machine learning (ML) artificial intelligence (AI). Models AI ML have shown promising solutions accelerating discovery optimization new antivirals or candidates. In present scenario, been extensively used drug research against SARS-COV-2 therapy discovery. This more useful identification potential existing drugs with inhibitory using datasets. computational approaches led speedy fight coronavirus. Therefore, paper suggests role field clinical trials vaccines practices tools.

Language: Английский

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Opportunities of artificial intelligence for supporting complex problem-solving: Findings from a scoping review

Computers and Education Artificial Intelligence, Journal Year: 2023, Volume and Issue: 4, P. 100138 - 100138

Published: Jan. 1, 2023

The research objective of this paper is to advance knowledge about the role artificial intelligence (AI) in complex problem-solving. A problem due large number highly inter-connected variables affecting state. Complex problem-solving situations often change decremental or worsen, forcing a solver act immediately, under considerable time pressure. While findings support assumption that (1) affective, (2) (meta-)cognitive, and (3) social processes problem-solving, opportunities AI for supporting need be further investigated. This article presents scoping review relevant literature from last five years. study included, N = 38 studies coding analysis. Our show addition increased publications, current trend suggests quality published work. Human-AI collaboration has been explored across broad variety application domains. However, four dimensions – namely, cognitive, metacognitive, affective - have augmented by different extent. Although most work done cognitive domain, it encouraging see progress as well. Implications future practice are being discussed.

Language: Английский

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A guide to current methodology and usage of reverse vaccinology towardsin silicovaccine discovery

FEMS Microbiology Reviews, Journal Year: 2023, Volume and Issue: 47(2)

Published: Feb. 16, 2023

Reverse vaccinology (RV) was described at its inception in 2000 as an silico process that starts from the genomic sequence of pathogen and ends with a list potential protein and/or peptide candidates to be experimentally validated for vaccine development. Twenty-two years later, this has evolved few steps entailing handful bioinformatics tools multitude plethora tools. Other related processes overlapping workflow have also emerged terms such subtractive proteomics, computational vaccinology, immunoinformatics. From perspective new RV practitioner, determining appropriate can time consuming overwhelming task, given number choices. This review presents current understanding usage research community determined by comprehensive survey scientific papers published last seven years. We believe mainstream presented here will valuable guideline all researchers wanting apply up-to-date discovery process.

Language: Английский

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Covid-19 and Artificial Intelligence: Genome sequencing, drug development and vaccine discovery

Journal of Infection and Public Health, Journal Year: 2022, Volume and Issue: 15(2), P. 289 - 296

Published: Jan. 19, 2022

To clarify the work done by using AI for identifying genomic sequences, development of drugs and vaccines COVID-19 to recognize advantages challenges such technology.A non-systematic review was done. All articles published on Pub-Med, Medline, Google, Google Scholar or digital health regarding sequencing, drug development, were scrutinized summarized.The sequence SARS- CoV-2 identified with help AI. It can also in prompt identification variants concern (VOC) as delta strains Omicron. Furthermore, there are many applied These included Atazanavir, Remdesivir, Efavirenz, Ritonavir, Dolutegravir, PARP1 inhibitors (Olaparib CVL218 which is Mefuparib hydrochloride), Abacavir, Roflumilast, Almitrine, Mesylate. Many developed utilizing new technology bioinformatics, databases, immune-informatics, machine learning, reverse vaccinology whole SARS-CoV-2 proteomes structural proteins. Examples these messenger RNA viral vector vaccines. provides cost-saving agility. However, its usage difficulty collecting data, internal external validation, ethical consideration, therapeutic effect, time needed clinical trials after approval. Moreover, a common problem deep learning (DL) model shortage interpretability.The growth techniques care opened broad gate discovering sequences virus VOC. helps (including repurposing) obtain potential preventive agents controlling pandemic.

Language: Английский

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Artificial Intelligence and Internet of Things (AI-IoT) Technologies in Response to COVID-19 Pandemic: A Systematic Review

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 62613 - 62660

Published: Jan. 1, 2022

The origin of the COVID-19 pandemic has given overture to redirection, as well innovation many digital technologies. Even after progression vaccination efforts across globe, total eradication this is still a distant future due evolution new variants. To proactively deal with pandemic, health care service providers and caretaker organizations require technologies, alongside improvements in existing related Internet Things (IoT), Artificial Intelligence (AI), Machine Learning terms infrastructure, efficiency, privacy, security. This paper provides an overview current theoretical application prospects IoT, AI, cloud computing, edge deep learning techniques, blockchain social networks, robots, machines, security techniques. In consideration these intersection we reviewed technologies within broad umbrella AI-IoT most concise classification scheme. review, illustrated that technological applications innovations have impacted field healthcare. essential found for healthcare were fog computing learning, blockchain. Furthermore, highlighted several aspects their impact novel methodology using techniques from image processing, machine differential system modeling.

Language: Английский

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COVID‐19: A systematic review and update on prevention, diagnosis, and treatment

MedComm, Journal Year: 2022, Volume and Issue: 3(1)

Published: Feb. 17, 2022

Abstract Since the rapid onset of COVID‐19 or SARS‐CoV‐2 pandemic in world 2019, extensive studies have been conducted to unveil behavior and emission pattern virus order determine best ways diagnosis thereof formulate effective drugs vaccines combat disease. The emergence novel diagnostic therapeutic techniques considering multiplicity reports from one side contradictions assessments other necessitates instantaneous updates on progress clinical investigations. There is also growing public anxiety time mutation COVID‐19, as reflected considerable mortality transmission, respectively, delta Omicron variants. We comprehensively review summarize different aspects prevention, diagnosis, treatment COVID‐19. First, biological characteristics were explained standpoint. Thereafter, preclinical animal models discussed frame symptoms effects patient with strategies in‐silico/computational biology. Finally, opportunities challenges nanoscience/nanotechnology identification, discussed. This covers almost all SARS‐CoV‐2‐related topics extensively deepen understanding latest achievements (last updated January 11, 2022).

Language: Английский

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COVID-19 Diagnosis: A Review of Rapid Antigen, RT-PCR and Artificial Intelligence Methods

Bioengineering, Journal Year: 2022, Volume and Issue: 9(4), P. 153 - 153

Published: April 3, 2022

As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused 5.3 deaths. Since the outbreak COVID-19, different methods, from medical to artificial intelligence, have been used for its detection, diagnosis, surveillance. Meanwhile, fast efficient point-of-care (POC) testing self-testing kits become necessary in fight against COVID-19 assist healthcare personnel governments curb spread virus. This paper presents a review various types detection diagnostic technologies, surveillance approaches that or proposed. The provided this article should be beneficial researchers field health policymakers at large.

Language: Английский

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Emerging technologies in public health campaigns: Artificial intelligence and big data

International Journal of Science and Research Archive, Journal Year: 2024, Volume and Issue: 11(1), P. 478 - 487

Published: Jan. 26, 2024

This research explores the integration of Artificial Intelligence (AI) and Big Data into public health campaigns, envisioning a future where precision, personalization, proactive interventions redefine healthcare. Analyzing transformative potential challenges, study examines AI's role in disease surveillance, diagnostics, predictive modeling, alongside Data's contributions to personalized comprehensive understanding. Ethical considerations, digital divide, regulatory frameworks are central necessitating delicate balance between innovation responsibility. The conclusion foresees healthcare landscape AI enhance effectiveness promising characterized by equitable, data-driven, resilient approaches address emerging challenges.

Language: Английский

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The Impact of Artificial Intelligence on Microbial Diagnosis

Microorganisms, Journal Year: 2024, Volume and Issue: 12(6), P. 1051 - 1051

Published: May 23, 2024

Traditional microbial diagnostic methods face many obstacles such as sample handling, culture difficulties, misidentification, and delays in determining susceptibility. The advent of artificial intelligence (AI) has markedly transformed diagnostics with rapid precise analyses. Nonetheless, ethical considerations accompany AI adoption, necessitating measures to uphold patient privacy, mitigate biases, ensure data integrity. This review examines conventional hurdles, stressing the significance standardized procedures processing. It underscores AI’s significant impact, particularly through machine learning (ML), diagnostics. Recent progressions AI, ML methodologies, are explored, showcasing their influence on categorization, comprehension microorganism interactions, augmentation microscopy capabilities. furnishes a comprehensive evaluation utility diagnostics, addressing both advantages challenges. A few case studies including SARS-CoV-2, malaria, mycobacteria serve illustrate potential for swift diagnosis. Utilization convolutional neural networks (CNNs) digital pathology, automated bacterial classification, colony counting further versatility. Additionally, improves antimicrobial susceptibility assessment contributes disease surveillance, outbreak forecasting, real-time monitoring. Despite limitations, integration microbiology presents robust solutions, user-friendly algorithms, training, promising paradigm-shifting advancements healthcare.

Language: Английский

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