arXiv:2605.16215v2 Announce Type: replace Abstract: Clinical decision support systems (CDSS) require scrutable, auditable pipelines that enable rigorous, reproducible validation. Yet current LLM-based CDSS remain largely opaque. Most "open" models are open-weight only, releasing parameters while withholding the data provenance, curation procedures, and generation pipelines that determine model behavior. Fully Open (FO) models, which expose the complete training stack end-to-end, do not currently exist in medicine. We introduce Fully Open Meditron, the first fully open pipeline for building LLM
The increasing deployment of LLMs in sensitive domains like clinical decision support necessitates greater transparency and audibility, a need that open-weight models have not yet fully addressed. This paper responds directly to the demand for explainable and verifiable AI systems in critical applications.
This development marks a significant step towards creating trustworthy AI for critical applications, pushing the boundaries of 'openness' beyond mere model parameters to include the entire development pipeline. It sets a new standard for transparency and reproducibility in clinical AI, which is crucial for adoption and regulatory approval.
The concept of 'open' in AI models for sensitive sectors is redefined, moving from just open-weight to 'fully open' pipelines that include data provenance and training procedures. This could lead to a new paradigm of verifiable and auditable AI systems, fostering trust and accelerating practical deployment.
- · Healthcare providers
- · Patients
- · AI researchers
- · Regulatory bodies
- · Closed-source clinical AI developers
- · Companies relying on opaque AI systems
Increased trust and adoption of LLM-based clinical decision support systems due to enhanced auditability.
A shift in regulatory frameworks demanding similar levels of transparency and auditability for AI in other sensitive sectors.
The development of new open-source ecosystems focused on 'fully open' methodologies across various AI applications, not just medicine.
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Read at arXiv cs.AI