Objectives: Development of an artificial intelligence algorithm for acne grading from smartphone photographs.
Introduction: We developed an artificial intelligence algorithm (AIA) for smartphones to determine the severity of facial acne using the GEA scale and to identify different types of acne lesion (comedonal, inflammatory) and postinflammatory hyperpigmentation (PIHP) or residual hyperpigmentation.
Materials / method: Overall, 5972 images (face, right and left profiles) obtained with smartphones (IOS and/or Android) from 1072 acne patients were collected. Three trained dermatologists assessed the acne severity for each patient. One acne severity grade per patient (grade given by the majority of the three dermatologists from the two sets of three images) was used to train the algorithm. Acne lesion identification was performed from a subgroup of 348 images using a tagging tool; tagged images served to train the algorithm.
Results: At final version 6, the GEA grading provided by AIA reached 68% and was similar to that provided by the dermatologists. Between version 4 and version 6, AIA improved precision results multiplied by 1.5 for inflammatory lesions, 2.5 for non-inflammatory lesions and by 2 for PIHP; recall was improved by 2.6, 1.6 and 2.7. The weighted average of precision and recall or F1 score was 84% for inflammatory lesions, 61% for non-inflammatory lesions and 72% for PIHP.
Conclusion: Development of the first artificial intelligence algorithm able to identify acne lesions and to grade the severity of the disease. Real benefit of these new tools, especially for the therapeutic education of patients.The final decision and the prescription should remain under the responsibility of the physician.
利益冲突声明
您有否接受任何资金来支持研究这个主题?
否
您是否接受过关于这项研究的任何酬金或其他报酬?
是
请注明名称(个人,公司,学会等等): Consulting fees from La Roche‐Posay Dermatological Laboratories to grade and analyze acne photographs
你是否和任何与您的研究所涉及的药物,材料或工具有密切联系的实体存在财务关系?
是
请注明名称(个人,公司,学会等等): Consulting fees from La Roche‐Posay Dermatological Laboratories to grade and analyze acne photographs
你是否拥有或者您已经为您此研究中的工具,药物或材料申请任何专利?
否
这项工作没有任何直接或间接的资金支持。由作者自己承担责任。