ArticleIEEE access : practical innovations, open solutions2022
Article in IEEE access : practical innovations, open solutions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed, 12 citations in OpenAlex.
- Eye-XAI: an explainable artificial intelligence approach for eye disease detection using symptom analysis.BMC medical informatics and decision making · 2025Article
- A secured remote patient monitoring framework for IoMT ecosystems.Scientific reports · 2025Article
- IoT-based bed and ventilator management system during the COVID-19 pandemic.Scientific reports · 2025Article
- Review
- Coalition of explainable artificial intelligence and quantum computing in precision medicine.Computational and structural biotechnology journal · 2025Review
- Revolutionizing healthcare: a comparative insight into deep learning's role in medical imaging.Scientific reports · 2024Article
- A comprehensive secure system enabling healthcare 5.0 using federated learning, intrusion detection and blockchain.PeerJ. Computer science · 2024Article
- Modeling Global Monkeypox Infection Spread Data: A Comparative Study of Time Series Regression and Machine Learning Models.Current microbiology · 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
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, healthcare stakeholders have orchestrated steps to strengthen and curb the COVID-19 wave. There has been a surge in vaccinations to curb the virus wave, but it is crucial to strengthen our healthcare resources to fight COVID-19 and like pandemics. Recent researchers have suggested effective forecasting models for COVID-19 transmission rate, spread, and the number of positive cases, but the focus on healthcare resources to meet the current spread is not discussed. Motivated from the gap, in this paper, we propose a scheme,
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.