ReviewPathogens (Basel, Switzerland)2021
Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19.
Review in Pathogens (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Literature review: Current trends and future prospects of digital vaccine supply chain support technology.Human vaccines & immunotherapeutics · 2025Pooled it
- [Medical education and artificial intelligence: perspectives and ethical challenges].Revista medica del Instituto Mexicano del Seguro Social · 2025Pooled it
- Artificial intelligence in vaccine research and development: an umbrella review.Frontiers in immunology · 2025Pooled it
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- Artificial intelligence for coordinating vaccine design, antiviral discovery, and real-world monitoring in the era of emerging and endemic viral threats.Frontiers in pharmacology · 2026Review
- Transforming therapeutics through biomaterials: A comprehensive insight into biomaterials' role in effective drug delivery and healthcare advancement.Biomaterials translational · 2026Review
- Mapping the landscape of AI and ML in vaccine innovation: A bibliometric study.Human vaccines & immunotherapeutics · 2025Article
- Large Language Models in Gastroenterology and Gastrointestinal Surgery: A New Frontier in Patient Communication and Education.Gastroenterology research · 2025Review
- Artificial intelligence and machine learning in the development of vaccines and immunotherapeutics-yesterday, today, and tomorrow.Frontiers in artificial intelligence · 2025Review
- Review
- The Impact of Artificial Intelligence on Microbial Diagnosis.Microorganisms · 2024Review
- RApid Throughput Screening for Asymptomatic COVID-19 Infection With an Electrocardiogram: A Prospective Observational Study.Mayo Clinic proceedings. Digital health · 2023Article
- Review
- The Epidemiology of Infectious Diseases Meets AI: A Match Made in Heaven.Pathogens (Basel, Switzerland) · 2023Article
- Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning.Journal of business research · 2023Article
- Impact of COVID-19 on Drug Discovery and Development: A Pharmacologist's Perspective.Advanced biomedical research · 2023Article
- Vaccine supply chain coordination using blockchain and artificial intelligence technologies.Computers & industrial engineering · 2023Article
- Prediction of Recurrent Mutations in SARS-CoV-2 Using Artificial Neural Networks.International journal of molecular sciences · 2022Article
- Biologic Functions of Hydroxychloroquine in Disease: From COVID-19 to Cancer.Pharmaceutics · 2022Review
- Medicine and machines.Medicine, health care, and philosophy · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic since the 1918 flu. The main challenges in mitigating COVID-19 are effective vaccination, treatment, and agile containment strategies. In this review, we focus on the potential of Artificial Intelligence (AI) in COVID-19 surveillance, diagnosis, outcome prediction, drug discovery and vaccine development. With the help of big data, AI tries to mimic the cognitive capabilities of a human brain, such as problem-solving and learning abilities. Machine Learning (ML), a subset of AI, holds special promise for solving problems based on experiences gained from the curated data. Advances in AI methods have created an unprecedented opportunity for building agile surveillance systems using the deluge of real-time data generated within a short span of time. During the COVID-19 pandemic, many reports have discussed the utility of AI approaches in prioritization, delivery, surveillance, and supply chain of drugs, vaccines, and non-pharmaceutical interventions. This review will discuss the clinical utility of AI-based models and will also discuss limitations and challenges faced by AI systems, such as model generalizability, explainability, and trust as pillars for real-life deployment in healthcare.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.