Virtual Patient Platform and Data Space for Sharing, Learning, Discussing, and Researching

André Santanchè, Heitor Soares Mattosinho, Marcos Felipe De Menezes Mota,Fagner Leal Pantoja, Gabriel De Freitas Leite, Ana Claudia Tonelli, Fernando Salvetti Valente, Juliana De Castro Solano Martins,Sandro Queirós, Tiago De Araujo Guerra Grangeia, Marco Antonio De Carvalho Filho

2023 IEEE 19th International Conference on e-Science (e-Science)(2023)

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摘要
As connected digital health data becomes more readily available, solutions are emerging to shorten the typical 17 years of latency in translating validated health knowledge into clinical practice. Learning Health Systems aims to achieve this goal. However, the proposed systems aim to address health data in a broad spectrum of data type variety. An open challenge is how to combine this variety around unification models. This work addresses a segment of this challenge by exploiting knowledge collected and built around Virtual Patients (VPs). VPs are a promising learning approach, providing interactive computer-based scenarios for solving clinical cases. Debate and resolution of clinical cases form the foundation of medical knowledge sharing and education. However, existing initiatives restrict their focus to a unidirectional method in which educators create these cases and learners play them. In this article, we show that we can expand the VP perspective toward a pivot model, which articulates learning and research initiatives, gathering together health knowledge. Our Jacinto platform and data space for sharing, learning, discussing, and researching clinical cases embodies this VP-centered approach. We present its effectiveness through a series of practical scenarios that explore and combine several knowledge pipelines.
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关键词
Electronic learning,Clinical diagnosis,Medical information systems,Virtual patient
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