ReviewJournal of medical systems2021
Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China.
Review in Journal of medical systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 3 of them syntheses that pooled it.
What it found
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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.
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Who cites it
29 citing papers in PubMed, 3 syntheses or guidelines pooled it, 72 citations in OpenAlex.
- Global perspectives on challenges, coping strategies, and future preparedness of nursing home staff during COVID-19: a systematic review and meta-synthesis.BMC health services research · 2025Pooled it
- Opportunities and challenges of artificial intelligence in public health: a systematic review on technological efficacy, ethical dilemmas, and governance pathways.Frontiers in public health · 2025Pooled it
- Global trends of big data analytics in health research: a bibliometric study.Frontiers in medicine · 2025Pooled it
- Ethical and Regulatory Challenges of Generative Artificial Intelligence in Healthcare: A Chinese Perspective.Journal of clinical nursing · 2026Article
- Artificial Intelligence in Public Health Education: A Scoping Review of Workforce Competency Development.Health science reports · 2026Article
- The application of AI-based interventions in diabetes personalized management: a systematic review and meta-analysis.Diabetology & metabolic syndrome · 2026Review
- Impact, use, and implications of artificial intelligence in public health decision making by elected officials: a scoping review.Frontiers in public health · 2026Article
- Personalized medication recommendations for Parkinson's disease patients using gated recurrent units and SHAP interpretability.Scientific reports · 2025Article
- Digital-based emergency prevention and control system: enhancing infection control in psychiatric hospitals.BMC medical informatics and decision making · 2025Article
- Development of a data-driven urban immunity assessment model: providing a new benchmark for urban governance under public health emergencies.Frontiers in public health · 2025Article
- Use of Digital Tools in Arbovirus Surveillance: Scoping Review.Journal of medical Internet research · 2024Article
- Salzburg Intensive Care database (SICdb): a detailed exploration and comparative analysis with MIMIC-IV.Scientific reports · 2024Article
- Identification of Early Warning Signals of Infectious Diseases in Hospitals by Integrating Clinical Treatment and Disease Prevention.Current medical science · 2024Article
- Application of artificial intelligence (AI) to control COVID-19 pandemic: Current status and future prospects.Heliyon · 2024Review
- Robust Medical Diagnosis: A Novel Two-Phase Deep Learning Framework for Adversarial Proof Disease Detection in Radiology Images.Journal of imaging informatics in medicine · 2024Article
- Decision making techniques in mass gathering medicine during the COVID-19 pandemia: a scoping review.Frontiers in public health · 2024Article
- Harnessing AI for public health: India's roadmap.Frontiers in public health · 2024Article
- Performance of an AI algorithm during the different phases of the COVID pandemics: what can we learn from the AI and vice versa.European journal of radiology open · 2023Article
- Learning from real world data about combinatorial treatment selection for COVID-19.Frontiers in artificial intelligence · 2023Article
- Artificial Intelligence-Driven Ensemble Model for Predicting Mortality Due to COVID-19 in East Africa.Diagnostics (Basel, Switzerland) · 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
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread rapidly and affected most of the world since its outbreak in Wuhan, China, which presents a major challenge to the emergency response mechanism for sudden public health events and epidemic prevention and control in all countries. In the face of the severe situation of epidemic prevention and control and the arduous task of social management, the tremendous power of science and technology in prevention and control has emerged. The new generation of information technology, represented by big data and artificial intelligence (AI) technology, has been widely used in the prevention, diagnosis, treatment and management of COVID-19 as an important basic support. Although the technology has developed, there are still challenges with respect to epidemic surveillance, accurate prevention and control, effective diagnosis and treatment, and timely judgement. The prevention and control of sudden infectious diseases usually depend on the control of infection sources, interruption of transmission channels and vaccine development. Big data and AI are effective technologies to identify the source of infection and have an irreplaceable role in distinguishing close contacts and suspicious populations. Advanced computational analysis is beneficial to accelerate the speed of vaccine research and development and to improve the quality of vaccines. AI provides support in automatically processing relevant data from medical images and clinical features, tests and examination findings; predicting disease progression and prognosis; and even recommending treatment plans and strategies. This paper reviews the application of big data and AI in the COVID-19 prevention, diagnosis, treatment and management decisions in China to explain how to apply big data and AI technology to address the common problems in the COVID-19 pandemic. Although the findings regarding the application of big data and AI technologies in sudden public health events lack validation of repeatability and universality, current studies in China have shown that the application of big data and AI is feasible in response to the COVID-19 pandemic. These studies concluded that the application of big data and AI technology can contribute to prevention, diagnosis, treatment and management decision making regarding sudden public health events in the future.
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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.