Use of a Preliminary Artificial Intelligence-Based Laryngeal Cancer Screening Framework for Low-Resource Settings: Development and Validation Study
This study demonstrated the feasibility of an AI-based screening framework designed for low-resource settings, showing its capability to triage patients for higher-level care efficiently. This approach promises substantial benefits for health care accessibility and patient outcomes in regions with limited specialist care in outpatient settings. This research provides necessary evidence to continue the development of a fully validated screening system for low-resource settings.
Authors
- Shao Wei Lam (ORCID: https://orcid.org/0000-0002-0898-5858)
- Walter T. Lee (ORCID: https://orcid.org/0000-0002-5487-3603)
- Hiang Khoon Tan (ORCID: https://orcid.org/0000-0002-8565-2926)
- Samuel Altonji (ORCID: https://orcid.org/0000-0002-9731-5601)
- Michael Dorosan (ORCID: https://orcid.org/0000-0002-6555-9281)
- Min Hun Lee (ORCID: https://orcid.org/0000-0003-3506-8972)
Institutions
- SingHealth (SG)
- Singapore General Hospital (SG)
- SingHealth Duke-NUS Academic Medical Centre (SG)
- National Cancer Centre Singapore (SG)
- Duke University Health System (US)
- Singapore Management University (SG)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2025-08-05
- DOI
- https://doi.org/10.2196/66110
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Duke-NUS Medical School
- National University of Singapore