In the last two weeks in ISM, I focused on a research paper that has significantly impacted the direction of my project. The paper, “Improving Skin Cancer Diagnostics through a Mobile App with a Large Interactive Image Repository (LIIR),” highlighted key areas like interactive training and real-time feedback, which I plan to integrate into my app. One of the biggest takeaways was the emphasis on how continuous learning tools helped primary care physicians (PCPs) improve diagnostic accuracy, particularly for challenging cases like dermal nevi and nodular melanoma. The study also stressed the importance of user engagement, noting how it dropped off after initial use. This insight will shape the gamification elements in my app, such as milestones and rewards, to keep users motivated. The findings on diagnostic errors, like misclassifications, gave me ideas for refining the AI feedback system, especially for ambiguous cases, ensuring the app can guide users more effectively. Additionally, the research reinforced my decision to include a longitudinal tracking feature, enabling users to monitor skin changes over time. The paper provided valuable direction for enhancing my app’s accuracy and user experience. By applying these insights, I am more confident that my project can aid in early skin cancer detection and engage users in a way that promotes long-term health awareness, supporting my goal of creating a tool that combines practicality with impact.
