OpenAlex
metadata only
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?
Artificial intelligence (AI) models are increasingly finding applications in the field of medicine. Concerns have been raised about the explainability of the decisions that are made by these AI models. In this article, we give a systematic analysis of explainable artificial intelligence (XAI), with
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
- Demystifying Artificial Intelligence: A Systematic Review of Explainable Artificial Intelligence in Medical Imaging.#9143
- Explainable Artificial Intelligence in Healthcare: Current Landscape, Challenges, and Future Directions.#122846
- Acceptance of Artificial Intelligence in Clinical Practice Among Chinese Physicians: Nationwide Cross-Sectional Survey Using Extended Unified Theory of Acceptance and Use of Technology and Explainable Machine Learning.#25683
- Explainability for artificial intelligence in healthcare: a multidisciplinary perspective#10580
- Explainability for artificial intelligence in healthcare: a multidisciplinary perspective#964267
Record · ID 964502
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