ArticleMachine learning2021
How artificial intelligence and machine learning can help healthcare systems respond to COVID-19.
Article in Machine learning, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 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
51 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence (AI) for social innovation in health education: promoting health literacy through personalized ai-driven learning tools - a systematic review.BMC medical education · 2025Pooled it
- Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2021Pooled it
- Anatomy-guided computational framework for classifying vascular ligation and lymphadenectomy in oncologic sigmoidectomy: toward AI-supported surgical auditing.International journal of colorectal disease · 2026Article
- Integrated counter current separation and omics approaches for discovery of bioactive compounds from medicinal plants.Frontiers in pharmacology · 2026Review
- A scoping review of future research trends and priorities in health systems.Health research policy and systems · 2025Article
- Cardiac Repair and Regeneration via Advanced Technology: Narrative Literature Review.JMIR biomedical engineering · 2025Review
- Use of artificial intelligence in healthcare in South Africa: A scoping review.Health SA = SA Gesondheid · 2025Review
- Validating Machine Learning Models Against the Saline Test Gold Standard for Primary Aldosteronism Diagnosis.JACC. Asia · 2024Article
- Multiple feature selection based on an optimization strategy for causal analysis of health data.Health information science and systems · 2024Article
- Benefits and Risks of AI in Health Care: Narrative Review.Interactive journal of medical research · 2024Review
- Implications of Big Data Analytics, AI, Machine Learning, and Deep Learning in the Health Care System of Bangladesh: Scoping Review.Journal of medical Internet research · 2024Article
- Spatio-temporal analysis of COVID-19 lockdown effect to survive in the US counties using ANN.Scientific reports · 2024Article
- Dynamic Price Application to Prevent Financial Losses to Hospitals Based on Machine Learning Algorithms.Healthcare (Basel, Switzerland) · 2024Article
- Detecting Parkinson's disease from shoe-mounted accelerometer sensors using convolutional neural networks optimized with modified metaheuristics.PeerJ. Computer science · 2024Article
- Exploring the impact of physiotherapy on health outcomes in older adults with chronic diseases: a cross-sectional analysis.Frontiers in public health · 2024Article
- Is the Cardiovascular Specialist Ready For the Fifth Revolution? The Role of Artificial Intelligence, Machine Learning, Big Data Analysis, Intelligent Swarming, and Knowledge-Centered Service on the Future of Global Cardiovascular Healthcare Delivery.Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists · 2023Article
- User Perspectives of Geriatric German Patients on Smart Sensor Technology in Healthcare.Sensors (Basel, Switzerland) · 2023Article
- Exploring Stakeholder Requirements to Enable Research and Development of Artificial Intelligence Algorithms in a Hospital-Based Generic Infrastructure: Results of a Multistep Mixed Methods Study.JMIR formative research · 2023Article
- A Review of the Machine Learning Algorithms for Covid-19 Case Analysis.IEEE transactions on artificial intelligence · 2023Article
- Exploring the matrix: knowledge, perceptions and prospects of artificial intelligence and machine learning in Nigerian healthcare.Frontiers in artificial intelligence · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
The COVID-19 global pandemic is a threat not only to the health of millions of individuals, but also to the stability of infrastructure and economies around the world. The disease will inevitably place an overwhelming burden on healthcare systems that cannot be effectively dealt with by existing facilities or responses based on conventional approaches. We believe that a rigorous clinical and societal response can only be mounted by using intelligence derived from a variety of data sources to better utilize scarce healthcare resources, provide personalized patient management plans, inform policy, and expedite clinical trials. In this paper, we introduce five of the most important challenges in responding to COVID-19 and show how each of them can be addressed by recent developments in machine learning (ML) and artificial intelligence (AI). We argue that the integration of these techniques into local, national, and international healthcare systems will save lives, and propose specific methods by which implementation can happen swiftly and efficiently. We offer to extend these resources and knowledge to assist policymakers seeking to implement these techniques.
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.