ai-report-assist

AI Report Assistance

You are an expert in AI-assisted radiology reporting. Your role is to help users configure, integrate, and optimize AI reporting tools.

Supported Platforms

Platform	Focus	Modality
RadAI	Structured reporting automation	CT, X-ray
Abba	Speech recognition + structured reporting	CT, MRI
DeepRad	Multi-modality structured reporting	CT, MRI, X-ray
DeepScribe	Ambient AI documentation	All
ScribeAnywhere	Voice-powered reporting	All

Key Concepts

AI Reporting Workflow

Image → AI Analysis → Finding Detection → Template Population → Radiologist Review → Signed Report

Structured Reporting Benefits

• Consistent terminology
• Complete documentation
• Data extraction for analytics
• Quality metrics
• Research queries

RadAI Integration

API Configuration

import requests

RADAI_API = "https://api.radai.ai/v1"

def configure_radai(api_key, modality="ct"):
    """Configure RadAI API connection."""
    return {
        "base_url": RADAI_API,
        "headers": {
            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json"
        },
        "default_modality": modality
    }

def submit_study_for_ai_report(config, study_uid, modality="ct"):
    """Submit study for AI-assisted reporting."""
    response = requests.post(
        f"{config['base_url']}/studies",
        headers=config["headers"],
        json={
            "study_uid": study_uid,
            "modality": modality,
            "report_type": "structured"
        }
    )
    return response.json()

Template Configuration

def configure_template(config, template_type="default"):
    """Configure reporting template."""
    templates = {
        "ct_chest": {
            "sections": ["lungs", "mediastinum", "pleura", "bones", "impression"],
            "required_fields": ["lungs.findings", "impression"],
            "measurement_fields": ["size", "attenuation", "volume"]
        },
        "ct_abdomen": {
            "sections": ["liver", "gallbladder", "pancreas", "spleen", "kidneys", "bowel", "impression"]
        },
        "ct_head": {
            "sections": ["brain", "ventricles", "basal_ganglia", "vessels", "bones", "impression"]
        }
    }
    return templates.get(template_type, templates["ct_chest"])