Research graph
References from Artificial Intelligence in Surgical Quality Improvement. Local targets link to admitted publications; unresolved targets remain external evidence.
Unresolved reference
External reference
Thirty years of medicare: impact on the covered population
1996 · External reference
Evaluating the quality of medical care. 1966
10.1111/j.1468-0009.2005.00397.x · 2005 · External reference
Committee to design a strategy for quality review and assurance in medicare; in, lohr KN. Defining quality of care
1990 · External reference
Unresolved reference
2001 · External reference
Unresolved reference
2006 · External reference
Applications of artificial intelligence (AI) in healthcare: a review
2021 · External reference
Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare
10.1038/s41746-022-00611-y · 2022 · External reference
Artificial intelligence in surgery: the future is now
2024 · External reference
Artificial intelligence and machine learning in prediction of surgical complications: current state, applications, and implications
10.1177/00031348221101488 · 2023 · External reference
Using society of thoracic surgeons risk models for risk-adjusting cardiac surgery results
10.1016/j.athoracsur.2009.10.078 · 2010 · External reference
A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm
10.1038/s41598-024-57700-z · 2024 · External reference
Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT
10.1007/s11547-023-01730-6 · 2024 · External reference
Machine-learning-based computed tomography radiomics regression model for predicting pulmonary function
10.1016/j.acra.2025.03.038 · 2025 · External reference
Preoperative and intraoperative risk factors associated with 30-day morbidity following urological surgery: the national surgical quality improvement program
10.1016/j.juro.2006.07.039 · 2006 · External reference
Consensus recommendations on how to assess the quality of surgical interventions
10.1038/s41591-023-02237-3 · 2023 · External reference
Acquisition and usage of robotic surgical data for machine learning analysis
10.1007/s00464-023-10214-7 · 2023 · External reference
Thoracic surgery video analysis for surgical phase recognition
2024 · External reference
Machine and deep learning for workflow recognition during surgery
10.1080/13645706.2019.1584116 · 2019 · External reference
EndoNet: a deep architecture for recognition tasks on laparoscopic videos
10.1109/tmi.2016.2593957 · 2017 · External reference
Automated analysis of operative video in surgical training: scoping review
10.1093/bjsopen/zrae124 · 2024 · External reference
Video-based performance analysis in pituitary surgery-part 1: surgical outcomes
10.1016/j.wneu.2024.07.218 · 2024 · External reference
Automated capture of intraoperative adverse events using artificial intelligence: a systematic review and meta-analysis
10.3390/jcm12041687 · 2023 · External reference
Validating the electronic cardiac arrest risk triage (eCART) score for risk stratification of surgical inpatients in the postoperative setting: retrospective cohort study
10.1097/sla.0000000000002665 · 2019 · External reference
Quick sepsis-related organ failure assessment, systemic inflammatory response syndrome, and early warning scores for detecting clinical deterioration in infected patients outside the intensive care unit
10.1164/rccm.201604-0854oc · 2017 · External reference
Artificial intelligence-based electrocardiogram model as a predictor of postoperative atrial fibrillation following cardiac surgery: retrospective cohort study
10.2196/77164 · 2025 · External reference
A clinical prediction model for prolonged air leak after pulmonary resection
10.1016/j.jtcvs.2016.10.003 · 2017 · External reference
Forecasting pulmonary air leak duration following lung surgery using transpleural airflow data from a digital pleural drainage device
10.21037/jtd.2018.08.11 · 2018 · External reference
Data-driven prediction of prolonged air leak after video-assisted thoracoscopic surgery for lung cancer: development and validation of machine-learning-based models using real-world data through the ePath system
2024 · External reference
External validation of a widely implemented proprietary sepsis prediction model in hospitalized patients
10.1001/jamainternmed.2021.2626 · 2021 · External reference
The trauma quality improvement program of the American College of Surgeons Committee on Trauma
10.1016/j.jamcollsurg.2009.07.001 · 2009 · External reference
Expanding the scope of quality measurement in surgery to include nonoperative care: results from the American College of Surgeons National Surgical Quality Improvement Program emergency general surgery pilot
10.1097/ta.0000000000001670 · 2017 · External reference
An audit and feedback system for effective quality improvement in head and neck surgery: can we become better surgeons?
10.1002/cncr.29238 · 2015 · External reference
Improving operating room efficiency: machine learning approach to predict case-time duration
10.1016/j.jamcollsurg.2019.05.029 · 2019 · External reference
A validated framework for responsible AI in healthcare autonomous systems
10.1038/s41598-025-25266-z · 2025 · External reference
End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
10.1038/s41591-019-0447-x · 2019 · External reference
Artificial intelligence and early warning systems
2020 · External reference
Dissecting racial bias in an algorithm used to manage the health of populations
10.1126/science.aax2342 · 2019 · External reference
Deep learning for healthcare: review, opportunities and challenges
10.1093/bib/bbx044 · 2018 · External reference
Responsibility and artificial intelligence
2020 · External reference
AI alignment: a comprehensive survey
2023 · External reference
