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Evidence-Based Clinical Reasoning for AI Agents — deterministic calculators, clinical guidelines, and MCP tools backed by DOI-traceable evidence.

Project description

Open Medicine

Evidence-Based Clinical Reasoning for AI Agents

PyPI Python License: MIT

LLMs hallucinate medical math and guidelines. Open Medicine stops them.

Open Medicine is an open-source Python library and MCP Server that provides deterministic, DOI-traceable clinical reasoning for AI agents. Every calculator, score, and guideline returns its scientific source—forcing agents to rely on verified clinical standards rather than latent knowledge.

Why Open Medicine?

If you ask an LLM to evaluate a clinical plan, it might casually agree with "aggressive fluid resuscitation" for a variceal bleed. This is a common, deadly hallucination.

By plugging the open-medicine-mcp server into your agent (via LangChain, AutoGPT, Claude Desktop, etc.), the agent can query the actual NICE CG141 Guidance and correct the plan: "Modify. Guidelines mandate a cautious, restrictive transfusion strategy (target Hgb 7-8 g/dL). Aggressive fluids will increase portal pressure."

Quick Start

1. Give your Agent an MD (MCP Server)

Expose the toolkit to any MCP-compatible agent:

npx @modelcontextprotocol/inspector open-medicine-mcp

2. Standalone Python Library

pip install open-medicine

Deterministic Clinical Calculators

from open_medicine.mcp.calculators.chadsvasc import calculate_chadsvasc, CHADSVAScParams

result = calculate_chadsvasc(CHADSVAScParams(
    age=72,
    hypertension=True,
    diabetes=False,
    congestive_heart_failure=False,
    stroke_tia_thromboembolism=True,
    vascular_disease=False,
    female_sex=False
))

print(result.value)             # 4
print(result.interpretation)    # "CHA2DS2-VASc score is 4. High risk..."
print(result.evidence.source_doi)  # "10.1161/CIR.0000000000001193"

Guideline Retrieval

from open_medicine.mcp.guideline_engine import search_guidelines, retrieve_guideline

# Search by topic
matches = search_guidelines("atrial fibrillation anticoagulation")

# Retrieve specific section
result = retrieve_guideline("acc_aha_af_2023", "anticoagulation")
print(result.evidence.source_doi)  # "10.1161/CIR.0000000000001193"

Available Tools (MCP)

Tool Purpose
search_clinical_calculators Find calculators by keyword (e.g., "GI bleed")
execute_clinical_calculator Run a calculator with JSON schema validation
search_guidelines Find guideline sections by topic
retrieve_guideline Retrieve curated, DOI-backed guideline content

Current Coverage

Calculators (54): AA Gradient, ABCD2, Anion Gap, Apixaban Dosing, ASCVD, BISAP, BMI, BSA (Mosteller), Canadian C-Spine, Caprini, CHA₂DS₂-VASc, Child-Pugh, CKD-EPI, Cockcroft-Gault, Corrected Calcium, Corrected QT, Corrected Sodium, CURB-65, Dabigatran Dosing, Edoxaban Dosing, Enoxaparin Dosing, FIB-4, Fisher Grade, GCS, Glasgow-Blatchford, GOLD COPD, GRACE, HAS-BLED, HEART Score, Heparin Dosing, Hunt & Hess, Insulin Basal Dosing, MELD-Na, NAFLD Fibrosis, NEWS2, NIHSS, Osmolar Gap, Padua, Parkland, PERC, qSOFA, Ranson's, Rivaroxaban Dosing, Rockall, Revised Trauma Score (RTS), Serum Osmolality, SOFA, TIMI STEMI, TIMI UA/NSTEMI, Warfarin Initiation, Wells' DVT, Wells' PE, Winter's Formula.

Guidelines (14):

  • ACC/AHA AF 2023 (acc_aha_af_2023)
  • KDIGO CKD 2024 (kdigo_ckd_2024)
  • BTS CAP 2009 (bts_cap_2009)
  • TIMI UA/NSTEMI 2000 (timi_ua_nstemi_2000)
  • ACC/AHA ASCVD 2013 (acc_aha_ascvd_2013)
  • Sepsis-3 2016 (sepsis3_2016)
  • Wells PE 2000 (wells_pe_2000)
  • GOLD COPD 2024 (gold_copd_2024)
  • AHA/ACC Chest Pain 2021 (aha_acc_chest_pain_2021)
  • AHA/ASA Ischemic Stroke 2019 (aha_asa_stroke_2019)
  • AASLD Cirrhosis 2023 (aasld_cirrhosis_2023)
  • ESC ACS 2023 (esc_acs_2023)
  • NICE UGIB 2012 (nice_ugib_2012)
  • RCP NEWS2 2017 (rcp_news2_2017)

Design Principles

  • Deterministic: Same input → same output. No LLM calls, no randomness.
  • Evidence-Backed: Every ClinicalResult includes a source_doi and evidence level.
  • FHIR-Compatible: Outputs include LOINC/SNOMED codes for direct integration with EHR systems.
  • Strictly Typed: Pydantic models validate all clinical inputs at the boundary.

License

MIT

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