ReviewJournal of cardiac surgery2021
Artificial intelligence and cardiac surgery during COVID-19 era.
Review in Journal of cardiac surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Big Data in cardiac surgery: real world and perspectives.Journal of cardiothoracic surgery · 2022Pooled it
- Innovation through Artificial Intelligence in Triage Systems for Resource Optimization in Future Pandemics.Biomimetics (Basel, Switzerland) · 2024Article
- Evaluating capabilities of large language models: Performance of GPT-4 on surgical knowledge assessments.Surgery · 2024Article
- Article
- The Impact of Artificial Intelligence on Optimizing Diagnosis and Treatment Plans for Rare Genetic Disorders.Cureus · 2023Review
- Evaluating Capabilities of Large Language Models: Performance of GPT4 on Surgical Knowledge Assessments.medRxiv : the preprint server for health sciences · 2023Article
- The future of Cardiothoracic surgery in Artificial intelligence.Annals of medicine and surgery (2012) · 2022Review
- The Development of Electronic Health and Artificial Intelligence in Surgery after the SARS-CoV-2 Pandemic-A Scoping Review.Journal of clinical medicine · 2021Article
- Artificial intelligence and cardiac surgery during COVID-19 era.Journal of cardiac surgery · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has increased the burden on hospital staff world-wide. Through the redistribution of scarce resources to these high-priority cases, the cardiac sector has fallen behind. In efforts to reduce transmission, reduction in direct patient-physician contact has led to a backlog of cardiac cases. However, this accumulation of postponed or cancelled nonurgent cardiac care seems to be resolvable with the assistance of technology. From telemedicine to artificial intelligence (AI), technology has transformed healthcare systems nationwide. Telemedicine enables patient monitoring from a distance, while AI unveils a whole new realm of possibilities in clinical practice, examples include: traditional systems replacement with more efficient and accurate processing machines; automation of clerical process; and triage assistance through risk predictions. These possibilities are driven by deep and machine learning. The two subsets of AI are explored and limitations regarding "big data" are discussed. The aims of this review are to explore AI: the advancements in methodology; current integration in cardiac surgery or other clinical scenarios; and potential future roles, which are innately nearing as the COVID-19 era urges alternative approaches for care.
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.