Development and Clinical Evaluation of an AI Support Tool for Improving Telemedicine Photo Quality

• URL: http://arxiv.org/abs/2209.09105v1
• Date: Mon, 12 Sep 2022 23:08:17 GMT
• Title: Development and Clinical Evaluation of an AI Support Tool for Improving Telemedicine Photo Quality
• Authors: Kailas Vodrahalli, Justin Ko, Albert S. Chiou, Roberto Novoa, Abubakar Abid, Michelle Phung, Kiana Yekrang, Paige Petrone, James Zou, Roxana Daneshjou
• Abstract summary: TrueImage 2.0 is an AI model for assessing patient photo quality for telemedicine. It provides real-time feedback to patients for photo quality improvement. TrueImage 2.0 reduced the number of patients with a poor-quality image by 68.0%.
• Score: 9.638614577248648
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Telemedicine utilization was accelerated during the COVID-19 pandemic, and skin conditions were a common use case. However, the quality of photographs sent by patients remains a major limitation. To address this issue, we developed TrueImage 2.0, an artificial intelligence (AI) model for assessing patient photo quality for telemedicine and providing real-time feedback to patients for photo quality improvement. TrueImage 2.0 was trained on 1700 telemedicine images annotated by clinicians for photo quality. On a retrospective dataset of 357 telemedicine images, TrueImage 2.0 effectively identified poor quality images (Receiver operator curve area under the curve (ROC-AUC) =0.78) and the reason for poor quality (Blurry ROC-AUC=0.84, Lighting issues ROC-AUC=0.70). The performance is consistent across age, gender, and skin tone. Next, we assessed whether patient-TrueImage 2.0 interaction led to an improvement in submitted photo quality through a prospective clinical pilot study with 98 patients. TrueImage 2.0 reduced the number of patients with a poor-quality image by 68.0%.

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