私たちは 'Model Dermatology' アルゴリズムを活用しており、その性能は複数の査読付き医学誌で検証・掲載されています。以下の国際的な機関と共同研究を実施しています:ソウル大学、延世大学、バーゼル大学、スタンフォード大学、MSKCC、オスペダーレ・サン・ボルトロ。代表的な出版物は以下をご参照ください。 - Assessment of Deep Neural Networks for the Diagnosis of Benign and Malignant Skin Neoplasms in Comparison with Dermatologists: A Retrospective Validation Study. PLOS Medicine, 2020 - Planet-wide Performance of a Skin Disease AI Algorithm Validated in Korea. npj Digital Medicine 2025
- Augmenting the Accuracy of Trainee Doctors in Diagnosing Skin Lesions Suspected of Skin Neoplasms in a Real-World Setting: A Prospective Controlled Before and After Study. PLOS One, 2022 - Performance of a deep neural network in teledermatology: a single center prospective diagnostic study. J Eur Acad Dermatol Venereol. 2020 - Augment Intelligence Dermatology : Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders. J Invest Dermatol. 2020 - Keratinocytic Skin Cancer Detection on the Face using Region-based Convolutional Neural Network. JAMA Dermatol. 2019 - Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm. J Invest Dermatol. 2018 - Evaluation of Artificial Intelligence-assisted Diagnosis of Skin Neoplasms – a single-center, paralleled, unmasked, randomized controlled trial. J Invest Dermatol. 2022>