Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone–Based Reading System
The AI-based program accurately interpreted urine test strips using smartphone cameras, offering an accessible and efficient method for urinalysis. This system can be used for immediate analysis and remote testing. Further research is warranted to refine test parameters such as specific gravity to enhance accuracy and reliability.
Authors
- Manmyung Kim
- H. Michael Zhang
- Hae-Ri Kim (ORCID: https://orcid.org/0000-0001-8766-6064)
- Qute Choi (ORCID: https://orcid.org/0000-0002-8520-3119)
- Jae Wan Jeon (ORCID: https://orcid.org/0000-0003-4256-3672)
- Hyun Jin Kim (ORCID: https://orcid.org/0000-0003-1725-2573)
- Yuri Seo (ORCID: https://orcid.org/0000-0001-6371-4025)
Institutions
- Chungnam National University (KR)
Publication Details
- Journal
- Annals of Laboratory Medicine
- Published
- 2024-12-16
- DOI
- https://doi.org/10.3343/alm.2024.0304
- Citations
- 4
- Primary Topic
- Mobile Health and mHealth Applications
- Type
- article
- Field-Weighted Citation Impact
- 3.40
Funders
- Chungnam National University
- Chungnam National University Hospital