arXiv (All)
open access
Communicating Uncertainty in AI-Supported Nurse Scheduling: Expert Co-Design and Evaluation of an Explainable AI Prototype
Nurse scheduling is a complex optimization problem in which nurses are assigned to shifts to meet staffing demands while complying with working-time limits, qualification requirements, and other operational and regulatory constraints. Artificial intelligence is increasingly being used to support thi
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
- Evaluating the Effectiveness of an AI-powered Physician Assistant in Improving Patients' and Physician's Satisfaction in an Outpatient Setting of a Tertiary Care Hospital.#835480
- Conceptualizing and evaluating the robustness of prediction models in healthcare#1166468
- Zetetic Algorithmic Monoculture#691459
- Model generalizability considerations in development and evaluation of SaMD#1120075
- Human-Governed Validation of Artificial Intelligence-Generated Medical Assessment Artifacts: A Technical Report.#1107482
Record · ID 1344177
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