Tschandl, Philipp

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

Tschandl, P., Rosendahl, C., & Kittler, H. (2018) · Scientific Data

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 3,628

Human-computer collaboration for skin cancer recognition

Tschandl, P., Rinner, C., Apalla, Z., Argenziano, G., Codella, N., Halpern, A., Janda, M., Lallas, A., Longo, C., Malvehy, J., et al. (2020) · Nature Medicine

Cutaneous Melanoma Detection and ManagementArtificial Intelligence in Healthcare and Education

Cited by 1,024

Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Codella, N., Rotemberg, V., Tschandl, P., Celebi, M. E., Dusza, S., Gutman, D., Helba, B., Kalloo, A., Liopyris, K., Marchetti, M., et al. (2019) · arXiv

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 984

Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study

Tschandl, P., Codella, N., Akay, B. N., Argenziano, G., Braun, R. P., Cabo, H., Gutman, D., Halpern, A., Helba, B., Hofmann-Wellenhof, R., et al. (2019) · The Lancet Oncology

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 555

Multimodal skin lesion classification using deep learning

Yap, J., Yolland, W., & Tschandl, P. (2018) · Experimental Dermatology

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 326

Accuracy of dermatoscopy for the diagnosis of nonpigmented cancers of the skin

Sinz, C., Tschandl, P., Rosendahl, C., Akay, B. N., Argenziano, G., Blum, A., Braun, R. P., Cabo, H., Gourhant, J.-Y., Kreusch, J., et al. (2017) · Journal of the American Academy of Dermatology

Cutaneous Melanoma Detection and ManagementNonmelanoma Skin Cancer Studies

Cited by 127

Accuracy of Computer-Aided Diagnosis of Melanoma: A Meta-analysis

Dick, V., Sinz, C., Mittlböck, M., Kittler, H., & Tschandl, P. (2019) · JAMA Dermatology

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 125

A Multimodal Vision Foundation Model for Clinical Dermatology

Yan, S., Yu, Z., Primiero, C., Vico-Alonso, C., Wang, Z., Yang, L., Tschandl, P., Hu, M., Ju, L., Tan, G., et al. (2025) · Nature Medicine

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 117

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

Tschandl, P. (2018) · Harvard Dataverse

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 71

Derm1M: A Million-scale Vision-Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology

Yan, S., Hu, M., Jiang, Y., Li, X., Fei, H., Tschandl, P., Kittler, H., & Ge, Z. (2025) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 13