This narrative review explored whether artificial intelligence and machine learning could improve care for patients with a strangulated small bowel obstruction. The review looked at dynamic, continuous predictive models compared to using static, isolated parameters. The goal was to support more accurate risk stratification to guide clinical decision-making.
The review did not report a specific sample size, study setting, or follow-up period. It also did not report any safety data, such as adverse events. The main focus was on the potential for AI to enhance triage precision and move management toward a more standardized, evidence-based approach.
A key limitation is the current lack of clinical validation and real-world applicability. This means the models have not been widely tested in actual hospital settings. The review does not prove that AI is better than current methods, only that it shows promise.
Readers should understand this is an early look at a potential tool. It is not a recommendation for immediate use. More research is needed to confirm if these models are safe and effective for guiding patient care.