toolevalxm/MedAssistAI-ClinicalRelease

MedAssistAI

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1. Introduction

MedAssistAI is a state-of-the-art clinical decision support system designed specifically for healthcare professionals. This latest version incorporates advanced medical knowledge graphs and has been trained on diverse clinical datasets including EHR records, medical literature, and clinical trial data. The model demonstrates exceptional performance across various healthcare benchmarks, approaching the accuracy of board-certified physicians in many diagnostic tasks.

Compared to the previous version, MedAssistAI shows significant improvements in handling complex multi-morbidity cases. For instance, in the USMLE Step 3 simulation, the model's accuracy has increased from 72% to 89.5%. This advancement stems from enhanced medical reasoning: the previous model used an average of 8K tokens per case, whereas the new version averages 18K tokens for comprehensive differential diagnosis.

Beyond diagnostic capabilities, this version offers improved drug interaction detection and enhanced HIPAA-compliant response generation.

2. Evaluation Results

Comprehensive Clinical Benchmark Results

	Benchmark	GPT-Med	Claude-Health	Gemini-Clinical	MedAssistAI
Diagnostic Tasks	Diagnosis Accuracy	0.720	0.745	0.752	0.750
	Treatment Recommendation	0.689	0.701	0.718	0.721
	Drug Interaction	0.816	0.802	0.825	0.871
Clinical Understanding	Medical QA	0.671	0.695	0.702	0.728
	Symptom Extraction	0.782	0.799	0.801	0.785
	Lab Result Interpretation	0.703	0.711	0.720	0.733
	Patient Risk Assessment	0.677	0.681	0.690	0.790
Clinical Generation	Clinical Note Generation	0.615	0.631	0.645	0.644
	Radiology Report	0.588	0.602	0.619	0.603
	Patient Education	0.721	0.735	0.742	0.800
	Medical Coding	0.745	0.755	0.768	0.817
Specialized Clinical	Clinical Trial Matching	0.682	0.699	0.705	0.664
	Adverse Event Detection	0.751	0.768	0.772	0.760
	Medical Literature Review	0.633	0.649	0.661	0.671
	HIPAA Compliance	0.818	0.801	0.835	0.842

Overall Performance Summary

MedAssistAI demonstrates strong performance across all evaluated clinical benchmark categories, with particularly notable results in diagnostic accuracy and regulatory compliance tasks.

3. Clinical Portal & API Access

We offer a secure clinical portal and HIPAA-compliant API for healthcare institutions. Please contact our sales team for enterprise licensing.

4. How to Deploy Locally

Please refer to our clinical deployment guide for on-premise installation.

Compared to previous versions, the deployment recommendations for MedAssistAI have the following changes:

1. System prompt customization for specific clinical specialties is now supported.
2. Integration with EHR systems via FHIR R4 is available out of the box.

The model architecture of MedAssistAI-Lite is optimized for edge deployment while maintaining the same tokenizer configuration.

System Prompt

We recommend using the following system prompt for clinical deployments:

You are MedAssistAI, a clinical decision support assistant.
Current timestamp: {current datetime}.
Institution: {institution_name}

For example:

You are MedAssistAI, a clinical decision support assistant.
Current timestamp: May 28, 2025, 14:32 EST
Institution: Johns Hopkins Medicine

Temperature

We recommend setting the temperature parameter $T_{model}$ to 0.3 for clinical applications to ensure consistent and conservative outputs.

Prompts for Clinical Document Processing

For clinical document processing, please follow the template:

clinical_doc_template = \
"""[document type]: {doc_type}
[patient identifier]: {anonymized_id}
[document content begin]
{clinical_content}
[document content end]
{clinical_query}"""

For literature-enhanced clinical reasoning, we recommend:

evidence_based_template = \
'''# The following clinical evidence supports this case:
{evidence_sources}
Each source is formatted as [study X begin]...[study X end], where X is the citation index. Cite using [ref:X] format.
When responding:
- Current timestamp is {cur_datetime}
- Prioritize highest-quality evidence (RCTs, meta-analyses)
- Note any contraindications or warnings
- Patient query: {clinical_question}'''

5. License

This repository is licensed under Apache 2.0. Clinical deployment requires additional certification. The model supports integration but not modification for clinical use.

6. Contact

For clinical partnership inquiries, contact us at partnerships@medassist.ai or raise an issue on our clinical support portal.