CNN-Based AI Model Targets Dermoscopic Risk Stratification of Basal Cell Carcinoma Subtypes — Trial of 2,500 Cases Opens in Istanbul
247 Health News Editorial
·16 July 2026
·5 min read
·clinical-trialsA new retrospective study from Istanbul Training and Research Hospital is developing a CNN-based AI model to classify basal cell carcinoma risk groups and predict histopathological subtypes from dermoscopic images across 2,500 confirmed cases. The trial aims to benchmark AI performance against practising dermatologists, with implications for pre-operative triage and surgical planning in one of the world's most common malignancies.
Originally reported by ClinicalTrials.gov
References
- 1.Istanbul Training and Research Hospital. (2025). Risk classification and prediction of histopathological subtypes in basal cell carcinoma using a CNN-based artificial intelligence model on dermoscopic images (NCT07677124). ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT07677124
- 2.Peris, K., Fargnoli, M. C., Garbe, C., Kaufmann, R., Bastholt, L., Seguin, N. B., Bataille, V., Marmol, V. D., Dummer, R., Harwood, C. A., Hauschild, A., Höller, C., Haedersdal, M., Malvehy, J., Middleton, M. R., Morton, C. A., Nagore, E., Stratigos, A. J., Szeimies, R. M., … Eggermont, A. M. M. (2019). Diagnosis and treatment of basal cell carcinoma: European consensus-based interdisciplinary guidelines. European Journal of Cancer, 118, 10–34. https://doi.org/10.1016/j.ejca.2019.06.003
- 3.Crowson, A. N. (2006). Basal cell carcinoma: biology, morphology and clinical implications. Modern Pathology, 19(Suppl 2), S127–S147. https://doi.org/10.1038/modpathol.3800512
- 4.Combalia, A., & Carrera, C. (2020). Dermoscopy of basal cell carcinoma: a systematic review of its diagnostic accuracy. Actas Dermo-Sifiliográficas, 111(8), 671–678. https://doi.org/10.1016/j.ad.2019.11.009
- 5.Therapeutic Goods Administration. (2023). Software as a medical device (SaMD): Guidance for industry. Australian Government Department of Health and Aged Care. https://www.tga.gov.au/resources/publication/guidance/software-medical-device-samd
- 6.Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118. https://doi.org/10.1038/nature21056
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247 Health News Editorial
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