P111 An AI-assisted similarity search engine for enhanced psoriasis case identification and patient engagement

Abstract Each psoriasis patient's clinical features follow a unique pattern that does not normally fit perfectly within classical subtypes of psoriasis as described in textbooks. The objective of this study is to develop an AI-assisted similarity search engine for psoriasis patients. This enables users to upload images and retrieve similar cases from both publicly available data, namely peer-reviewed literature and public datasets, and a private collection. With a match, a patient may glean additional information about his or her personal subtype of psoriasis including potential treatment strategies, and even get in touch with other patients affected with a similar clinical pattern. The system is designed to be self-hosted, thereby enabling patients to share their own images through the completion of an informed consent form. The types of psoriasis covered are plaque-type, guttate, inverse, erythrodermic, pustular and mixed. The system offers the option of linking to similar images of lesions by manually selecting an area of interest. Furthermore, the system is capable of suggesting similarities to differential diagnoses, i.e. eczema or pityriasis rubra pilaris. The tool is intended for use by patients, general physicians and dermatologists, with the objective of enhancing patients' understanding of their conditions and facilitating discussion and exchange through an integrated forum. The system employs visual transformers as feature extractors to vectorize the uploaded images and utilizes cosine similarity to compare them with images in the database. Furthermore, supplementary data, such as sparse matching, is presented to the user in order to facilitate a deeper comprehension of the similarities between the images in question. Furthermore, the system is capable of displaying supplementary data regarding the cases stored in the database, as well as links to pertinent literature. Should they so desire, patients are afforded the opportunity to interact with other patients who have been diagnosed with similar conditions, thereby facilitating discussion of their respective cases. The preliminary findings suggest that this tool has the potential to markedly enhance patients' comprehension of their conditions, while also enabling them to utilize the tool for diagnostic assistance. Furthermore, patients can gain deeper insights into their condition, which may facilitate informed discussions and community support through the forum. The system has the potential to transform psoriasis management by providing a reliable, user-friendly platform for case comparison and patient engagement. Further research will focus on expanding the database and refining the algorithm to enhance its diagnostic capabilities and user experience.