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oai:data.mendeley.com/fh7sk5ksmk.2 2023-08-08T01:02:29Z

Tan, Eugene Supplemental Online Content - Development and validation of a deep learning model for improving detection of non-melanoma skin carcinomas treated with Mohs micrographic surgery Mendeley Data Supplemental Online Content sTable 1. CLEAR Derm statement. sTable 2. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. sFigure 3. Convolutional Neural Network Image Classification with a Deep Learning Model Architecture. sFigure 4. Evaluation of Model Performance for Lesion Detection in Mohs frozen section Images. sFigure 5. Evaluation of concordance in pathology review. sTable 6. Evaluation of leave-one-out cross-validation for patient-level performance in the development cohort. sTable 7. Performance of prediction models in temporal validation cohort stratified by BCC subtypes. Artificial Intelligence Skin Cancer Mohs Surgery Deep Learning Lim, Sophie Lamont, Duncan Lim, David Epstein, Richard Lin, Frank Dataset doi:10.17632/fh7sk5ksmk.2 oai:data.mendeley.com/fh7sk5ksmk.2 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/fh7sk5ksmk 2023-08-08T01:02:29Z