Browsing by Author "Aguero, Rosario"

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    The Impact of Melanoma Imaging Biomarker Cues on Detection Sensitivity and Specificity in Melanoma versus Clinically Atypical Nevi
    (2024) Aguero, Rosario; Buchanan, Kendall L.; Navarrete-Dechent, Cristian; Marghoob, Ashfaq A.; Stein, Jennifer A.; Landy, Michael S.; Leachman, Sancy A.; Linden, Kenneth G.; Garcet, Sandra; Krueger, James G.; Gareau, Daniel S.
    Simple Summary Early detection of melanoma and differentiation from benign nevi can be challenging even for the most experienced dermatologists. To improve melanoma detection, artificial intelligence algorithms incorporating dermoscopy have been developed, but lack transparency and therefore have limited training value for healthcare providers. To address this, an automated approach utilizing imaging biomarker cues (IBCs), logical features extracted from images that mimic expert dermatologists' dermoscopic pattern recognition skills, was developed. This study excluded deep learning approaches to which IBCs are complementary or alternative. Ten participants assessed 78 dermoscopic images (39 melanomas and 39 nevi) first without IBCs and then with IBCs. Using IBCs significantly improved diagnostic accuracy: sensitivity increased significantly from 73.69% to 81.57% (p = 0.0051) and specificity increased from 60.50% to 67.25% (p = 0.059). These results indicate that incorporating IBCs can significantly enhance melanoma diagnosis, with potential implications for improved screening practices. Further research is needed to confirm these findings across a variety of healthcare providers.Abstract 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.
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    Use of game-based learning strategies for dermatology and dermoscopy education: a cross-sectional survey of members of the International Dermoscopy Society
    (2024) Donoso, Francisca; Peirano, Dominga; Aguero, Rosario; Longo, Caterina; Apalla, Zoe; Lallas, Aimilios; Jaimes, Natalia; Navarrete-Dechent, Cristian
    Background Dermoscopy is a valuable tool in the diagnosis of various skin conditions. It increases sensitivity and specificity in skin cancer diagnosis, as well as in infectious, inflammatory and hair diseases. However, mastering the intricacies of dermoscopy can be challenging. In this context, innovative educational methods are sought, including game-based learning (GBL) strategies. Objectives To describe current perceptions, knowledge and use of GBL strategies in dermoscopy education, and identify strengths and challenges to enhance their use. Methods A web-based cross-sectional survey with 25 questions was distributed to members of the International Dermoscopy Society between October 2022 and April 2023. Responses were collected and analysed using frequency analysis and graphical representation. Results In total, 801 responses were received. Of these, 46.6% of respondents were unfamiliar with gamification and serious games. Among those acquainted with these concepts, 56.3% reported using GBL strategies for education. Younger participants were more likely to use GBL strategies (P = 0.02). Participants familiar with GBL believed it enhanced medical education (78.5%) but should not entirely replace traditional teaching methods (96.0%). For dermoscopy education specifically, 22.1% of respondents had used GBL strategies, with Kahoot! (35.5%) and YOUdermoscopy (24.1%) being the most commonly used platforms. Respondents found gaming strategies to be fun (95.5%), motivating (91.0%) and valuable for e-learning (94.4%). Conclusions Results from this survey demonstrate a favourable perception of GBL strategies in dermatology education, including dermoscopy. While there are ongoing challenges in validation, GBL strategies are promising and valuable tools that can aid the learning and teaching experience. Addressing implementation barriers and validating existing games could optimize the impact of GBL on dermatology education.