Developing AI-Driven Digital Health Solutions: A Comprehensive Scoping Review
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By
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Shuimei Liu
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L. Raymond Guo
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September 12, 2026
Clinical Scorecard: Developing AI-Driven Digital Health Solutions: A Comprehensive Scoping Review
At a Glance
| Category | Detail |
| Condition | AI-Driven Digital Health Solutions |
| Key Mechanisms | Integration of Generative AI and Large Language Models in health tool design and development. |
| Target Population | Diverse patient populations with heterogeneous needs. |
| Care Setting | Digital health interventions and health informatics. |
Key Highlights
- AI is transitioning from a product to a collaborative design agent in digital health.
- Generative AI tools are reshaping prototyping workflows and patient engagement.
- A systematic scoping review was conducted to explore AI's roles in health design methodologies.
- Existing literature lacks comprehensive insights into AI's operational workflows in health tool design.
- A practical framework for incorporating AI agents in health informatics is proposed.
Guideline-Based Recommendations
Diagnosis
Management
Monitoring & Follow-up
Risks
Patient & Prescribing Data
Not specified; focuses on diverse patient populations.
Emphasizes the need for culturally adaptive health content co-created with marginalized communities.
Clinical Best Practices
- Incorporate human-in-the-loop validation stages in AI-driven design workflows.
- Utilize established frameworks like CONSORT-AI and SPIRIT-AI for assessing AI models.
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