Artificial intelligence in three-dimensional total-body photography for skin cancer surveillance
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By
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Kai Liang Lew
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Kok Swee Sim
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Wai Ti Chan
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July 6, 2026
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Clinical Scorecard: Utilizing Artificial Intelligence with Three-Dimensional Total-Body Imaging for Monitoring Skin Cancer
At a Glance
| Category | Detail |
|---|
| Condition | Skin Cancer |
| Key Mechanisms | Artificial intelligence-assisted three-dimensional total-body photography for lesion detection and monitoring. |
| Target Population | Patients undergoing skin cancer surveillance. |
| Care Setting | Clinical dermatology practice. |
Key Highlights
- AI can enhance lesion detection across the whole body rather than focusing on individual lesions.
- Three-dimensional total-body photography supports longitudinal monitoring and risk assessment.
- Current evidence on AI-assisted 3D TBP remains limited and requires further validation.
Guideline-Based Recommendations
Diagnosis
- Utilize AI-assisted 3D TBP for comprehensive skin examination.
Management
- Implement automated triage and lesion detection to improve workflow.
Monitoring & Follow-up
- Adopt longitudinal tracking of lesions for better patient outcomes.
Risks
- Address issues related to dataset transparency, false positives, and equity in AI applications.
Patient & Prescribing Data
Individuals at risk for skin cancer, including those with multiple lesions.
AI-assisted tools can facilitate early detection and timely intervention.
Clinical Best Practices
- Integrate 3D TBP into routine skin cancer screening protocols.
- Focus on patient-level risk assessment rather than solely lesion-level accuracy.
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