ReviewPatterns (New York, N.Y.)2021
On the role of artificial intelligence in medical imaging of COVID-19.
Review in Patterns (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers, 3 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
25 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial intelligence in liver cancer research: a scientometrics analysis of trends and topics.Frontiers in oncology · 2024Pooled it
- Automated COVID-19 diagnosis and prognosis with medical imaging and who is publishing: a systematic review.Physical and engineering sciences in medicine · 2022Pooled it
- Application of artificial intelligence in diagnosing COVID-19 disease symptoms on chest X-rays: A systematic review.International journal of medical sciences · 2022Pooled it
- Using deep learning systems for diagnosing common skin lesions in sexual health.Communications medicine · 2025Article
- Utilizing artificial intelligence as an arbitrary tool in managing difficult COVID-19 cases in critical care medicine.World journal of critical care medicine · 2025Review
- Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study.Journal of medical Internet research · 2024Article
- Evaluation of artificial intelligence-powered screening for sexually transmitted infections-related skin lesions using clinical images and metadata.BMC medicine · 2024Article
- Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.BMC health services research · 2024Article
- Improving long COVID-related text classification: a novel end-to-end domain-adaptive paraphrasing framework.Scientific reports · 2024Article
- Article
- A historical perspective of biomedical explainable AI research.Patterns (New York, N.Y.) · 2023Review
- Discovering associations between radiological features and COVID-19 patients' deterioration.Health science reports · 2023Article
- Training certified detectives to track down the intrinsic shortcuts in COVID-19 chest x-ray data sets.Scientific reports · 2023Article
- Efficient Lung Ultrasound Classification.Bioengineering (Basel, Switzerland) · 2023Article
- Training certified detectives to track down the intrinsic shortcuts in COVID-19 chest x-ray data sets.Research square · 2023Article
- Institutional Strategies to Maintain and Grow Imaging Research During the COVID-19 Pandemic.Academic radiology · 2023Review
- Organoids revealed: morphological analysis of the profound next generation in-vitro model with artificial intelligence.Bio-design and manufacturing · 2023Review
- Developing medical imaging AI for emerging infectious diseases.Nature communications · 2022Article
- Modern views of machine learning for precision psychiatry.Patterns (New York, N.Y.) · 2022Review
- Stabilizing deep tomographic reconstruction: Part A. Hybrid framework and experimental results.Patterns (New York, N.Y.) · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although a plethora of research articles on AI methods on COVID-19 medical imaging are published, their clinical value remains unclear. We conducted the largest systematic review of the literature addressing the utility of AI in imaging for COVID-19 patient care. By keyword searches on PubMed and preprint servers throughout 2020, we identified 463 manuscripts and performed a systematic meta-analysis to assess their technical merit and clinical relevance. Our analysis evidences a significant disparity between clinical and AI communities, in the focus on both imaging modalities (AI experts neglected CT and ultrasound, favoring X-ray) and performed tasks (71.9% of AI papers centered on diagnosis). The vast majority of manuscripts were found to be deficient regarding potential use in clinical practice, but 2.7% (n = 12) publications were assigned a high maturity level and are summarized in greater detail. We provide an itemized discussion of the challenges in developing clinically relevant AI solutions with recommendations and remedies.
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.