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Crowdsourcing Knowledge Discovery and Innovations in Medicine

机译:众包医学发现和创新

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Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous and seemingly insolvable questions. But these groups tend to work in isolated environments, and do not communicate or interact effectively. Clinicians are typically buried in the weeds and exigencies of daily practice such that they do not recognize or act on ways to improve knowledge discovery. Researchers may not be able to identify the gaps in clinical knowledge. For data scientists, the main challenge is discerning what is relevant in a domain that is both unfamiliar and complex. Each type of domain expert can contribute skills unavailable to the other groups. “Health hackathons” and “data marathons”, in which diverse participants work together, can leverage the current ready availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented, but functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled.
机译:在根据研究得出的现有证据不能很好解决的情况下,临床医生面临艰难的治疗决策。医学数字化为临床医生提供了与研究人员和数据科学家合作解决先前模棱两可,似乎无法解决的问题的机会。但是这些团体倾向于在孤立的环境中工作,并且无法有效地交流或互动。临床医生通常被埋在日常实践的杂草和紧急状态中,因此他们不认识或不采取行动来改善知识发现。研究人员可能无法识别临床知识方面的差距。对于数据科学家而言,主要挑战是辨别在既陌生又复杂的领域中相关的内容。每种类型的领域专家都可以贡献其他团队无法获得的技能。不同参与者共同参与的“健康黑客马拉松”和“数据马拉松”可以利用当前可用的数字数据来发现新知识。利用这些才华横溢但功能划分的团队的互补技能和专长,在系统级别制定创新。结果,知识发现过程同时实现了民主化和改善,解决了实际问题,支持了跨学科协作,并实现了创新。

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