NCBI PubMed Central
open access
Artificial intelligence and machine learning for prediction of postoperative complications: A systematic review focused on anesthesiology, perioperative risk stratification, and clinical applicability.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- ASA Prediction Using Health Data and Medication Use#831713
- Machine learning and artificial intelligence for clinical prediction in orthopaedic surgery: a bibliometric analysis of 1,739 publications, 2015–2026#447724
- Machine learning-based prediction models for postoperative pulmonary complications in elderly patients undergoing abdominal surgery.#412213
- The Cutting Edge: A Systematic Review of Artificial Intelligence and Machine Learning in Predicting Esophagectomy Outcomes.#678321
- Predicting ICU Mortality in ARDS Patients#803805
Record · ID 1501059
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive