AIMC Topic: Surgical Procedures, Operative

Clear Filters Showing 21 to 30 of 103 articles

Development and preliminary assessment of a machine learning model to predict myocardial infarction and cardiac arrest after major operations.

Resuscitation
INTRODUCTION: Accurate prediction of complications often informs shared decision-making. Derived over 10 years ago to enhance prediction of intra/post-operative myocardial infarction and cardiac arrest (MI/CA), the Gupta score has been criticized for...

Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study.

International journal of surgery (London, England)
BACKGROUND: Early identification of patients at high-risk of postoperative acute kidney injury (AKI) can facilitate the development of preventive approaches. This study aimed to develop prediction models for postoperative AKI in noncardiac surgery us...

Generative artificial intelligence in surgery.

Surgery
Generative artificial intelligence is able to collect, extract, digest, and generate information in an understandable way for humans. As the first surgical applications of generative artificial intelligence are applied, this perspective paper aims to...

Ethical and legal issues regarding artificial intelligence (AI) and management of surgical data.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
The advent of AI in surgical practice is representing a major innovation. As its role expands and due to its several implications, strict compliance with ethical, legal and regulatory good practices is mandatory. Observance of ethical principles and ...

Multicentre validation of a machine learning model for predicting respiratory failure after noncardiac surgery.

British journal of anaesthesia
BACKGROUND: Postoperative respiratory failure is a serious complication that could benefit from early accurate identification of high-risk patients. We developed and validated a machine learning model to predict postoperative respiratory failure, def...

The State of Artificial Intelligence in Pediatric Surgery: A Systematic Review.

Journal of pediatric surgery
BACKGROUND: Artificial intelligence (AI) has been recently shown to improve clinical workflows and outcomes - yet its potential in pediatric surgery remains largely unexplored. This systematic review details the use of AI in pediatric surgery.

Concept Graph Neural Networks for Surgical Video Understanding.

IEEE transactions on medical imaging
Analysis of relations between objects and comprehension of abstract concepts in the surgical video is important in AI-augmented surgery. However, building models that integrate our knowledge and understanding of surgery remains a challenging endeavor...

Federated Cycling (FedCy): Semi-Supervised Federated Learning of Surgical Phases.

IEEE transactions on medical imaging
Recent advancements in deep learning methods bring computer-assistance a step closer to fulfilling promises of safer surgical procedures. However, the generalizability of such methods is often dependent on training on diverse datasets from multiple m...