SynthesisInternational journal of medical sciences2022
Application of artificial intelligence in diagnosing COVID-19 disease symptoms on chest X-rays: A systematic review.
Synthesis in International journal of medical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis 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
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Differences of the Chest Images Between Coronavirus Disease 2019 (COVID-19) Patients and Influenza Patients: A Systematic Review and Meta-analysis.International journal of medical sciences · 2025Pooled it
- Application and prospect of artificial intelligence in diagnostic imaging of prostate cancer.NPJ digital medicine · 2026Review
- Limitations in Chest X-Ray Interpretation by Vision-Capable Large Language Models, Gemini 1.0, Gemini 1.5 Pro, GPT-4 Turbo, and GPT-4o.Diagnostics (Basel, Switzerland) · 2026Article
- Use of Artificial Intelligence in Public Health Education for Pandemic Preparedness and Response.Annals of global health · 2026Review
- 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
- Automatic measurement of X-ray radiographic parameters based on cascaded HRNet model from the supraspinatus outlet radiographs.Quantitative imaging in medicine and surgery · 2025Article
- Independent evaluation of the accuracy of 5 artificial intelligence software for detecting lung nodules on chest X-rays.Quantitative imaging in medicine and surgery · 2024Article
- Special Types of Breast Cancer: Clinical Behavior and Radiological Appearance.Journal of imaging · 2024Review
- Evaluation of the Performance of an Artificial Intelligence (AI) Algorithm in Detecting Thoracic Pathologies on Chest Radiographs.Diagnostics (Basel, Switzerland) · 2024Article
- Can Artificial Intelligence Replace Humans for Detecting Lung Tumors on Radiographs? An Examination of Resected Malignant Lung Tumors.Journal of personalized medicine · 2024Article
- Clinical characteristics of COVID-19 patients treated in emergency COVID-19 hospitals in Vietnam: Experience from Phutho province, Vietnam.International journal of medical sciences · 2024Article
- Generative Adversarial Network (Generative Artificial Intelligence) in Pediatric Radiology: A Systematic Review.Children (Basel, Switzerland) · 2023Review
- COVID-19 recognition from chest X-ray images by combining deep learning with transfer learning.Digital healthArticle
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 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This systematic review focuses on using artificial intelligence (AI) to detect COVID-19 infection with the help of X-ray images.
Indexed as
Identifiers
What Socratic 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 Socratic graph.