ReviewComputational and structural biotechnology journal2021
Artificial intelligence in clinical care amidst COVID-19 pandemic: A systematic review.
Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
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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
53 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI Quality Standards in Health Care: Rapid Umbrella Review.Journal of medical Internet research · 2024Pooled it
- Use of Artificial Intelligence in the Early Diagnosis of Oral Cancer: Current Update, Limitations and Future Perspectives.Journal of dentistry (Shiraz, Iran) · 2026Article
- Enhancing pandemic surveillance and testing: a simulation modeling study utilizing german multicenter data with federated machine learning.Health care management science · 2026Article
- Predicting sepsis prognosis using deep learning with routine biomarkers.Frontiers in medicine · 2026Article
- A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis.Journal of medical Internet research · 2025Article
- Calculating the Risk of Admission to Intensive Care Units in COVID-19 Patients Using Machine Learning.Journal of clinical medicine · 2025Article
- A Comprehensive Drift-Adaptive Framework for Sustaining Model Performance in COVID-19 Detection From Dynamic Cough Audio Data: Model Development and Validation.Journal of medical Internet research · 2025Article
- An overview of reviews on digital health interventions during COVID- 19 era: insights and lessons for future pandemics.Archives of public health = Archives belges de sante publique · 2025Article
- Enhancing clinical decision-making in closed pelvic fractures with machine learning models.Biomolecules & biomedicine · 2025Article
- Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques.Scientific reports · 2025Article
- The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.Molecular biomedicine · 2025Review
- Predicting Severe Respiratory Failure in Patients with COVID-19: A Machine Learning Approach.Journal of clinical medicine · 2024Article
- Radiomics models to predict bone marrow metastasis of neuroblastoma using CT.Cancer innovation · 2024Article
- Predictive models-assisted diagnosis of AIDS-associated Pneumocystis jirovecii pneumonia in the emergency room, based on clinical, laboratory, and radiological data.Scientific reports · 2024Article
- AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods.Osong public health and research perspectives · 2024Article
- Personalized Assessment of Mortality Risk and Hospital Stay Duration in Hospitalized Patients with COVID-19 Treated with Remdesivir: A Machine Learning Approach.Journal of clinical medicine · 2024Article
- Exploring the feasibility of an artificial intelligence based clinical decision support system for cutaneous melanoma detection in primary care - a mixed method study.Scandinavian journal of primary health care · 2024Article
- Application of artificial intelligence (AI) to control COVID-19 pandemic: Current status and future prospects.Heliyon · 2024Review
- The prediction of influenza-like illness using national influenza surveillance data and Baidu query data.BMC public health · 2024Article
- May Artificial Intelligence take health and sustainability on a honeymoon? Towards green technologies for multidimensional health and environmental justice.Global bioethics = Problemi di bioetica · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in>3 million deaths so far. Improving early screening, diagnosis and prognosis of the disease are critical steps in assisting healthcare professionals to save lives during this pandemic. Since WHO declared the COVID-19 outbreak as a pandemic, several studies have been conducted using Artificial Intelligence techniques to optimize these steps on clinical settings in terms of quality, accuracy and most importantly time. The objective of this study is to conduct a systematic literature review on published and preprint reports of Artificial Intelligence models developed and validated for screening, diagnosis and prognosis of the coronavirus disease 2019. We included 101 studies, published from January 1st, 2020 to December 30th, 2020, that developed AI prediction models which can be applied in the clinical setting. We identified in total 14 models for screening, 38 diagnostic models for detecting COVID-19 and 50 prognostic models for predicting ICU need, ventilator need, mortality risk, severity assessment or hospital length stay. Moreover, 43 studies were based on medical imaging and 58 studies on the use of clinical parameters, laboratory results or demographic features. Several heterogeneous predictors derived from multimodal data were identified. Analysis of these multimodal data, captured from various sources, in terms of prominence for each category of the included studies, was performed. Finally, Risk of Bias (RoB) analysis was also conducted to examine the applicability of the included studies in the clinical setting and assist healthcare providers, guideline developers, and policymakers.
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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.