Springer Nature OA
open access
CC BY-NC-ND 4.0
Human-Informed Neural Networks (HINNs): Trust-Adaptive Learning with Expert Guidance
Artificial intelligence (AI) is increasingly deployed in domains where decisions carry substantial ethical, financial, regulatory, and clinical consequences. Conventional neural networks are commonly trained using fixed data-driven objective functions that may fail to represent the complexity of hum
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
- Artificial Intelligence as a Challenge for Modern Medicine and Law#1176298
- Third-party governance and artificial intelligence for diabetes management in primary health care, China.#421289
- Reproducible macroscopic dynamics in a closed-loop human-AI learning system#622532
- Architecture of the “No”: Structural Intelligence (SI) as the Organization of Form Under Pressure#165218
- Ethical Issues of Risk Management Disclosure in Healthcare Networks.#136070
Record · ID 1082024
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