Validate DxEngine diagnostic accuracy across lab data, clinical cases, and LLM comparisons.
npx skills add https://github.com/BEC01/dxengine --skill eval-bec01
Please help me install this Agent Skill. Skill: eval Source: https://github.com/BEC01/dxengine/tree/main/.claude/skills/eval Command: npx skills add https://github.com/BEC01/dxengine --skill eval-bec01
This Skill enables users to validate and benchmark the performance and safety of DxEngine's diagnostic reasoning capabilities across multiple evaluation layers.
Run the evaluation suite to measure DxEngine's accuracy on lab data, clinical cases, compare with LLMs, and verify thresholds by executing the appropriate commands.
High-intent search queries and answers about installing and using this skill.
You can validate medical AI diagnostic tools by running a comprehensive multi-layer evaluation suite that tests lab accuracy, assesses clinical cases, benchmarks against language models, and verifies automated thresholds.
Multi-layer evaluation for healthcare AI systematically validates diagnostic reasoning across lab analyte classification, real and simulated clinical cases, and automated regression tests to ensure safety and robustness.
You can benchmark diagnostic reasoning models against large language models by executing automated comparison tests that evaluate accuracy and safety across diverse patient demographics and clinical cases.
Yes, the evaluation suite supports automated threshold verification by running regression tests to ensure system integrity and diagnostic accuracy over time across medical AI applications.
Yes, you can use the lab accuracy testing layer to validate analyte classification correctness across diverse patient demographics to ensure diagnostic safety and reliability.
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