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Multi-Modal Healthcare Diagnosis System

Design an ML system for clinical decision support that integrates multiple data modalities.

Scenario: A hospital system wants to assist radiologists and physicians with diagnostic support. The system ingests medical images (X-rays, CT), lab results, patient history, and clinical notes to suggest possible diagnoses and flag urgent findings.

Your Task: Design the multi-modal diagnostic support system.

Key Challenges:

Multi-modal fusion (images + structured data + text)
Explainability requirements (clinicians must understand why)
Regulatory compliance (FDA approval, audit trails)
Safety: never suppress critical findings
Handling missing modalities (not all patients have all data)

Design Mode

📝 Your Design Approach

Describe your system design approach. Consider components, data flow, and key decisions.

🎯 Design Questions(Select all that apply)

Q1.How should the system integrate multiple data modalities (imaging, lab results, clinical notes)?

Q2.What is critical for clinical AI model validation?

Q3.How should the system handle missing modalities (e.g., patient has no imaging)?

Q4.What is essential for clinical AI explainability?

0 of 4 questions answered

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