ReviewJAMA surgery2020
Artificial Intelligence and Surgical Decision-making.
Review in JAMA surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 249 papers, 5 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
249 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Artificial intelligence applications in surgical education and training: a systematic review.Frontiers in artificial intelligence · 2026Pooled it
- Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review.BMC musculoskeletal disorders · 2025Pooled it
- Artificial intelligence models in the surgical planning of low-grade gliomas: a systematic review.Frontiers in oncology · 2025Pooled it
- Machine learning, deep learning and hernia surgery. Are we pushing the limits of abdominal core health? A qualitative systematic review.Hernia : the journal of hernias and abdominal wall surgery · 2024Pooled it
- Behaviour, barriers and facilitators of shared decision making in breast cancer surgical treatment: A qualitative systematic review using a 'Best Fit' framework approach.Health expectations : an international journal of public participation in health care and health policy · 2024Pooled it
- Efficiency assessment of intelligent patient-specific instrumentation in total knee arthroplasty: a prospective randomized controlled trial.Journal of orthopaedic surgery and research · 2024Trial
- Advanced systems for intraoperative cartilage evaluation and treatment demonstrate early feasibility and a shift towards integrating artificial intelligence: A scoping review.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Article
- Artificial intelligence in orthopaedics should be built with surgeons, not just for them!Journal of experimental orthopaedics · 2026Article
- Electronic Health Record Workflows in Acute Care Surgery: Ethnographic Study.JMIR medical informatics · 2026Article
- Artificial intelligence in abdominal wall hernia surgery: clinical applications and translational readiness.Surgical endoscopy · 2026Review
- Role of artificial intelligence in head and neck surgery - A narrative review.Turkish journal of surgery · 2026Article
- Application of artificial intelligence-generated clinical cases in case-based learning of histology and embryology.Anatomical sciences education · 2026Article
- Artificial Intelligence Scribes in Orthopaedic Surgery: A Narrative Review.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Review
- [Application of artificial intelligence for surgical skill assessment and quality control in minimally invasive surgery: progress, problems and prospect].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Review
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- Reinforcement Learning for Intraoperative Hypotension Management with Consideration to Postoperative Acute Kidney Injury.Kidney360 · 2026Article
- Navigating Oral Cancer Management: Combining Artificial Intelligence and Clinical Guidelines for Optimal Decision-Making.International archives of otorhinolaryngology · 2026Article
- A multimodal feature disentanglement model for lymphadenopathy diagnosis based on BUS and CDFI ultrasound videos: a retrospective, prospective, multicenter study.European radiology · 2026Article
- Advanced machine learning-based screening for primary aldosteronism with plasma steroids, potassium, and renin.NPJ digital medicine · 2026Article
- Algorithmic bias in surgical risk prediction models and its impact on patient safety: a review.Patient safety in surgery · 2026Review
189 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Importance: Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes that artificial intelligence should be used to augment surgical decision-making. Observations: Surgical decision-making is dominated by hypothetical-deductive reasoning, individual judgment, and heuristics. These factors can lead to bias, error, and preventable harm. Traditional predictive analytics and clinical decision-support systems are intended to augment surgical decision-making, but their clinical utility is compromised by time-consuming manual data management and suboptimal accuracy. These challenges can be overcome by automated artificial intelligence models fed by livestreaming electronic health record data with mobile device outputs. This approach would require data standardization, advances in model interpretability, careful implementation and monitoring, attention to ethical challenges involving algorithm bias and accountability for errors, and preservation of bedside assessment and human intuition in the decision-making process. Conclusions and Relevance: Integration of artificial intelligence with surgical decision-making has the potential to transform care by augmenting the decision to operate, informed consent process, identification and mitigation of modifiable risk factors, decisions regarding postoperative management, and shared decisions regarding resource use.
Indexed as
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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.