ArticleThe American surgeon2023
Artificial Intelligence and Machine Learning in Prediction of Surgical Complications: Current State, Applications, and Implications.
Article in The American surgeon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 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
48 citing papers in PubMed, 1 synthesis or guideline pooled it, 107 citations in OpenAlex.
- Colorectal cancer treatment assisted by robotic platforms - a systematic review.Journal of robotic surgery · 2026Pooled it
- AI Trustworthiness in the Perioperative Period for Patients with Serious Illness: Scoping Narrative Review.JMIR perioperative medicine · 2026Article
- Artificial Intelligence for Predicting Postoperative Outcomes in Anterior Segment and Ocular Adnexa Surgery: A Systematic Review.Ophthalmology science · 2026Review
- Adding Artificial Intelligence to the Surgeon's Domain.World journal of surgery · 2026Review
- Integration of Precision Medicine into ERAS Pathways: A Conceptual Framework, Current Feasibility and Challenges.Journal of personalized medicine · 2026Review
- Algorithmic bias in surgical risk prediction models and its impact on patient safety: a review.Patient safety in surgery · 2026Review
- Review
- Artificial intelligence for surgical management of benign esophageal disease: scoping review and evidence mapping.Langenbeck's archives of surgery · 2026Article
- IFSO Survey: Use of Large Language Models (LLMs) by Metabolic Bariatric Surgeons and Integrated Health Professionals.Obesity surgery · 2026Article
- The role of artificial intelligence in advancing urologic care: From diagnostics to therapeutics.Surgery in practice and science · 2026Review
- Development and comparison of machine learning models for predicting postoperative ileus after posterior thoracolumbar fracture surgery.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Review
- Artificial Intelligence in Adult Cardiovascular Medicine and Surgery: Real-World Deployments and Outcomes.Journal of personalized medicine · 2026Review
- Artificial intelligence in surgical planning and outcome prediction for obstructive sleep apnea: emerging hype or the future standard?Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Review
- The complex task of modelling artificial intelligence workflows for forecasting postoperative risk.Journal of anesthesia, analgesia and critical care · 2025Article
- Development of a machine learning-based nomogram for predicting chronic postsurgical pain after uniportal video-assisted thoracoscopic surgery.Journal of thoracic disease · 2025Article
- Artificial intelligence in pancreatitis: A narrative review on advancing precision diagnosis, prognosis, and therapeutic strategies.World journal of gastroenterology · 2025Review
- Generative artificial intelligence, large language models and ChatGPT in musculoskeletal Oncology: Current applications and future potential.Journal of clinical orthopaedics and trauma · 2025Article
- Artificial Intelligence in Bariatric Surgery: Optimizing Personalized Decision-Making, Predictive Monitoring, and Postoperative Outcomes.Obesity surgery · 2025Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
Abstract
Surgical complications pose significant challenges for surgeons, patients, and health care systems as they may result in patient distress, suboptimal outcomes, and higher health care costs. Artificial intelligence (AI)-driven models have revolutionized the field of surgery by accurately identifying patients at high risk of developing surgical complications and by overcoming several limitations associated with traditional statistics-based risk calculators. This article aims to provide an overview of AI in predicting surgical complications using common machine learning and deep learning algorithms and illustrates how this can be utilized to risk stratify patients preoperatively. This can form the basis for discussions on informed consent based on individualized patient factors in the future.
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.