Incorporation of dermoscopy and artificial intelligence (AI) is improving healthcare professionals’ ability to diagnose melanoma earlier, but these algorithms often suffer from a “black box” issue, where decision-making processes are not transparent, limiting their utility for training healthcare providers. To address this, an automated approach for generating melanoma imaging biomarker cues (IBCs), which mimics the screening cues used by expert dermoscopists, was developed. This study created a one-minute learning environment where dermatologists adopted a sensory cue integration algorithm to combine a single IBC with a risk score built on many IBCs, then immediately tested their performance in differentiating melanoma from benign nevi. Ten participants evaluated 78 dermoscopic images, comprised of 39 melanomas and 39 nevi, first without IBCs and then with IBCs. Participants classified each image as melanoma or nevus in both experimental conditions, enabling direct comparative analysis through paired data. With IBCs, average sensitivity improved significantly from 73.69% to 81.57% (p= 0.0051), and the average specificity improved from 60.50% to 67.25% (p= 0.059) for the diagnosis of melanoma. The index of discriminability (d′) increased significantly by 0.47 (p= 0.002). Therefore, the incorporation of IBCs can significantly improve physicians’ sensitivity in melanoma diagnosis. While more research is needed to validate this approach across other healthcare providers, its use may positively impact melanoma screening practices.
皮肤镜与人工智能（AI）的结合提升了医疗专业人员早期诊断黑色素瘤的能力，但这些算法常存在“黑箱”问题，其决策过程缺乏透明度，限制了其在培训医疗人员方面的应用价值。为解决这一问题，本研究开发了一种自动生成黑色素瘤影像生物标志物提示（IBCs）的方法，该方法模拟了专业皮肤镜医师使用的筛查线索。研究构建了一个一分钟学习环境，皮肤科医生在此环境中采用感官线索整合算法，将单一IBC与基于多个IBC构建的风险评分相结合，随后立即测试其区分黑色素瘤与良性痣的能力。十名参与者评估了78张皮肤镜图像（包括39例黑色素瘤和39例痣），首先在没有IBC辅助的条件下进行判断，随后在IBC辅助下再次评估。参与者在两种实验条件下对每张图像进行黑色素瘤或痣的分类，从而通过配对数据实现直接比较分析。结果显示，使用IBC后，黑色素瘤诊断的平均灵敏度从73.69%显著提升至81.57%（p=0.0051），平均特异度从60.50%提高至67.25%（p=0.059）。判别指数（d′）显著增加了0.47（p=0.002）。因此，IBC的整合能显著提升医生诊断黑色素瘤的灵敏度。虽然仍需更多研究以验证该方法在其他医疗从业者中的适用性，但其应用可能对黑色素瘤筛查实践产生积极影响。
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