ArticleAnnals of surgery2023
Artificial Intelligence-enabled Decision Support in Surgery: State-of-the-art and Future Directions.
Article in Annals of surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
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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
36 citing papers in PubMed.
- Effects of explainable artificial intelligence in neurology decision support.Annals of clinical and translational neurology · 2024Trial
- Human-Centered design requirements for clinical decision support in cardiac surgery perfusion.Human factors in healthcare · 2026Article
- Artificial intelligence in orthopaedics should be built with surgeons, not just for them!Journal of experimental orthopaedics · 2026Article
- Decision-centered artificial intelligence for perioperative care outside the operating room: a practical review for surgeons.Journal of minimally invasive surgery · 2026Review
- Artificial intelligence and chatbots in general surgery: a survey among surgeons in Germany, Austria and Switzerland.Surgical endoscopy · 2026Article
- Towards clinically interpretable machine learning in emergency surgery: feature importance and insights across clinical time points in abdominal pain cases.Langenbeck's archives of surgery · 2026Article
- Predicting Hungry Bone Syndrome with Interpretable Machine Learning: A Single-Center Cohort of Dialysis Patients Undergoing Parathyroidectomy.Diagnostics (Basel, Switzerland) · 2026Article
- Risk prediction in spine surgery: a scoping review of traditional models, artificial intelligence, and the challenge of clinical translation.Spine deformity · 2026Review
- Artificial Intelligence Language Models in Oncology: A Cross-Sectional Analysis of Published Studies.Cureus · 2026Review
- Physical AI goes to the operating room: are we ready for the Surgical Data Factory?Annals of surgical treatment and research · 2026Review
- Review
- Artificial Intelligence in Oncologic Thoracic Surgery: Clinical Decision Support and Emerging Applications.Cancers · 2026Review
- Comparative analysis of six large language models in perioperative decision support for geriatric patients with multimorbidity: a three-dimensional evaluation framework.BMC anesthesiology · 2026Article
- Large registries, rare outcomes and neutral/inconclusive machine learning results in abdominal wall surgery.Journal of abdominal wall surgery : JAWS · 2026Article
- Artificial intelligence and big data for precision regenerative medicine in knee osteoarthritis: endotyping, responder prediction, and clinical translation.Frontiers in bioengineering and biotechnology · 2026Review
- PICO-based assessment and categorization of evidence for digital health interventions: an inductive framework development.Frontiers in digital health · 2026Review
- Study - International multicentric minimally invasive liver resection (SIMMILR-4) : a comparison of conventional, digitally enhanced and collaborative robotic with Tele-robotic laparoscopic surgery for colorectal liver metastases.Journal of robotic surgery · 2025Article
- Implementation of artificial intelligence (AI) in ASD treatment.North American Spine Society journal · 2025Article
- Accuracy and Reliability of Artificial Intelligence in Surgical Decision-Making: A Literature Review.Cureus · 2025Review
- Emerging innovation, artificial intelligence, and digital technology in esophagology.Annals of the New York Academy of Sciences · 2025Review
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Authors and funding
13 authors.
Funding
Abstract
objectiveTo summarize state-of-the-art artificial intelligence-enabled decision support in surgery and to quantify deficiencies in scientific rigor and reporting.
backgroundTo positively affect surgical care, decision-support models must exceed current reporting guideline requirements by performing external and real-time validation, enrolling adequate sample sizes, reporting model precision, assessing performance across vulnerable populations, and achieving clinical implementation; the degree to which published models meet these criteria is unknown.
methodsEmbase, PubMed, and MEDLINE databases were searched from their inception to September 21, 2022 for articles describing artificial intelligence-enabled decision support in surgery that uses preoperative or intraoperative data elements to predict complications within 90 days of surgery. Scientific rigor and reporting criteria were assessed and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.
resultsSample size ranged from 163-2,882,526, with 8/36 articles (22.2%) featuring sample sizes of less than 2000; 7 of these 8 articles (87.5%) had below-average (<0.83) area under the receiver operating characteristic or accuracy. Overall, 29 articles (80.6%) performed internal validation only, 5 (13.8%) performed external validation, and 2 (5.6%) performed real-time validation. Twenty-three articles (63.9%) reported precision. No articles reported performance across sociodemographic categories. Thirteen articles (36.1%) presented a framework that could be used for clinical implementation; none assessed clinical implementation efficacy.
conclusionsArtificial intelligence-enabled decision support in surgery is limited by reliance on internal validation, small sample sizes that risk overfitting and sacrifice predictive performance, and failure to report confidence intervals, precision, equity analyses, and clinical implementation. Researchers should strive to improve scientific quality.
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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.