Block 1 - Schedule Property Monitoring
- Type / Role
- n8n-nodes-base.scheduleTrigger - scheduleTrigger
- Config choices
- Version 1.3
How It Works This workflow automates medical imaging analysis and diagnostic reporting for radiology departments, imaging centers, and hospital networks managing high patient volumes. Designed for ...
n8n-nodes-base.scheduletrigger, n8n-nodes-base.set, n8n-nodes-base.httprequest, n8n-nodes-base.merge, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.switch
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.
Original n8n.io sourceThis workflow automates medical imaging analysis and diagnostic reporting for radiology departments, imaging centers, and hospital networks managing high patient volumes. Designed for radiologists, medical imaging technicians, and diagnostic coordinators, it solves the challenge of rapidly analyzing imaging studies, prioritizing critical findings, routing cases appropriately, and generating structured reports while maintaining diagnostic accuracy and regulatory compliance. The system triggers on new imaging studies, fetches imagery and metadata, prepares data through AI agents (Validation ensures image quality and completeness), calculates risk scores, routes by validation status and risk level through multiple pathways, deploys specialized AI agents for comprehensive analysis (Orchestration coordinates findings, Google Calendar manages scheduling, Slack Tool enables team communication, Email Actions handles notifications, Water Monitoring tracks contrast protocols, Compliance Validation ensures regulatory adherence, Leave Management coordinates radiologist availability), and generates final diagnostic reports with complete audit trails. Organizations reduce diagnosis turnaround time by 60%, improve critical finding detection rates, ensure consistent reporting standards, and enable radiologists to focus on complex cases requiring expert judgment.
PACS/VNA system API access, HIPAA-compliant AI service accounts
Emergency radiology triage (stroke, trauma), lung nodule detection and tracking
Modify AI models for modality-specific analysis (CT, MRI, X-ray, ultrasound)
Reduces diagnosis turnaround time by 60%, improves critical finding detection rates
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 38 workflow blocks. Download the JSON for the full node graph.
| Workflow | Validate property compliance risk and orchestrate actions with OpenAI, Google Calendar, Gmail, Slack, and Google Sheets |
|---|---|
| Complexity | advanced |
| Nodes | 38 |
| Categories | Document Extraction, AI Summarization |
| Author | Cheng Siong Chin |
| Published | 12 Feb 2026 |
Use the JSON export at /data/workflows/13338/13338.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
How It Works This workflow automates medical imaging analysis and diagnostic reporting for radiology departments, imaging centers, and hospital networks managing high patient volumes. Designed for ...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction, AI Summarization use case.