Radiomics-Based AI Model to Assist Clinicians in Intracranial Hemorrhage Diagnosis: External Validation Study
When applied to an external dataset, the accuracy of the AI model in categorizing spontaneous ICHs based on radiomics decreased. However, using the model as an assistant substantially improved the performance of all reader groups, including trainees and radiology and nonradiology specialists.
Authors
- Papangkorn Inkeaw (ORCID: https://orcid.org/0000-0002-3630-1564)
- Thanwa Sudsang (ORCID: https://orcid.org/0009-0002-9821-4535)
- Chaisiri Angkurawaranon (ORCID: https://orcid.org/0000-0003-4206-9164)
- Chakri Madla (ORCID: https://orcid.org/0000-0002-3435-6369)
- Salita Angkurawaranon (ORCID: https://orcid.org/0000-0001-6211-5717)
- Kittisak Unsrisong (ORCID: https://orcid.org/0000-0001-8363-978X)
- Patrinee Traisathit (ORCID: https://orcid.org/0000-0003-2918-1928)
- Withawat Vuthiwong (ORCID: https://orcid.org/0000-0002-7531-7999)
- Phattanun Thabarsa (ORCID: https://orcid.org/0009-0002-0193-9485)
- Natipat Jitmahawong (ORCID: https://orcid.org/0009-0001-0192-2387)
Institutions
- Mahidol University (TH)
- Ramathibodi Hospital (TH)
- Chiang Mai University (TH)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2025-12-11
- DOI
- https://doi.org/10.2196/81038
- Primary Topic
- Intracerebral and Subarachnoid Hemorrhage Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00