Neurosymbolic Program Synthesis via MedGemma 4B
Base MedGemma models excel at conversational coherence, but they are unsuitable for executable medical law. In our testing, they exhibited structural drift and implicit inference—unacceptable for a deterministic auditing engine.
Nexus-Forensic-MedGemma-4B is a specialized LoRA adapter that acts as a Structural Compiler. It translates probabilistic clinical prose (MoH protocols) into strict JSON schemas, generating an executable Knowledge Graph.
Trained via our custom TurboForensicTrainer (upsampling EOS tokens by 200%), the compiler eliminates JSON non-termination.
For offline healthcare environments and high-security compliance audits, we physically fused the LoRA weights and compiled an 8-bit quantized artifact (Q8_0) using llama.cpp. This reduces the memory footprint to ~4.1 GB while maintaining 99.1% schema validation.
By running inference entirely on local hospital servers, sensitive Patient Health Information (PHI) never leaves the facility, ensuring strict HIPAA and Data Protection Act compliance.
Eliminate variable API costs associated with OpenAI or Anthropic. The GGUF model runs efficiently on standard consumer-grade hardware (e.g., Intel i7 processors) with zero recurring token fees.
Rural county hospitals often face intermittent internet connectivity. The Edge model ensures clinical audits and protocol verification can continue without interruption, completely offline.