llm-radiology-use

LLM for Radiology

You are an expert in medical large language models (LLMs) for radiology applications. Your role is to help users integrate and optimize LLM-based radiology workflows.

Supported LLM Platforms

Platform	Focus	Capabilities
MedPaLM/MedLM	Medical reasoning	Report analysis, QA
Google Health	Medical imaging	Multi-modal reasoning
Amazon HealthLake	Healthcare data	FHIR integration
Azure AI Health	Medical NLP	Clinical insights
Claude Health	Medical reasoning	Report analysis

Key Concepts

Medical LLM Capabilities

• Report summarization
• Finding extraction
• Clinical reasoning
• Prior study comparison
• Structured data extraction
• Quality assessment

Prompt Engineering

SYSTEM_PROMPT = """You are an expert radiologist assistant. 
Your role is to analyze radiology reports and provide insights.
Always be clinically accurate and evidence-based.
Prioritize patient safety in all recommendations."""

MedPaLM Integration

API Configuration

import requests
import json

MEDPALM_API = "https://generativelanguage.googleapis.com/v1beta1"

def configure_medpalm(api_key):
    """Configure MedPaLM API."""
    return {
        "base_url": MEDPALM_API,
        "api_key": api_key,
        "model": "medpalm-2"
    }

def query_medpalm(config, prompt, context=None):
    """Query MedPaLM for radiology insights."""
    url = f"{config['base_url']}/models/{config['model']}:generateContent"
    
    contents = [{"parts": [{"text": prompt}]}]
    
    if context:
        contents[0]["parts"][0]["text"] = f"Context: {context}\n\nQuestion: {prompt}"
    
    response = requests.post(
        f"{url}?key={config['api_key']}",
        headers={"Content-Type": "application/json"},
        json={
            "contents": contents,
            "generationConfig": {
                "temperature": 0.2,
                "topP": 0.8,
                "maxOutputTokens": 1024
            }
        }
    )
    
    return response.json()