Despite enormous enthusiasm, machine learning models are rarely translated into clinical care and there is minimal evidence of clinical or economic impact. New conference venues and academic journals have emerged to promote the proliferating research; however, the translational path remains unclear. This review undertakes the first in-depth study to identify how machine learning models that ingest structured electronic health record data can be applied to clinical decision support tasks and translated into clinical practice. The authors complement their own work with the experience of 21 machine learning products that address problems across clinical domains and across geographic populations. Four phases of translation emerge: design and develop, evaluate and validate, diffuse and scale, and continuing monitoring and maintenance. The review highlights the varying approaches taken across each phase by teams building machine learning products and presents a discussion of challenges and opportunities. The translational path and associated findings are instructive to researchers and developers building machine learning products, policy makers regulating machine learning products, and health system leaders who are considering adopting a machine learning product.
Technical communicators need to be to be life-long-learners and comprehensive visionariexWe are responsive to the current environment but constantly scan the horizon 10 see political, social, economical, cultural, and market trends. We oflen set and lead agendas. Perceptive technical communicators seek to develop collaborative relationships with both creators oj'data and the end users of that information.In this worhhop we will explore the Lafitte!D %cy Model of Engagement. Using participatory exercises in small group communities, we will have the opportunity to enrich our approach to our next technical communication project. We will learn how to expand our skills of interaction and creatively turn data into understandable, usefir1 information that will be accepted by our audiences. Exercises will encourage us to shape and send dramatic and memorable messages using metaphors and analogies. We will iden@ ways to translate coniplex concepts io reflect our audience's "maps of the world. I' Emphasis is on oral presentations including web presentations and videoconferencing.This experiential workshop emphasizes the value of integrating diverse personalities, nationalities, and professional skills into collaborative relationships. Communication and cooperation are not just idealistic concepts but important business issues. We, as technical communicators, play an important role in making these relationships successful. Scientists, engineers and technology experts must be able to understand and work together harmoniously whether creating new software or operating the international space station. It is also critical for these specialists to carry on a dialogue with the general public if they are to gain acceptance for their ideas. Companies battling to gain a competitive advantage and organizations fighting for funding must be able to translate the latest technological and scientific findings for the benefit of colleagues, partners, customers, investors, and other key decision-makers. Academicians need to prepare their students with real-world skills for professional survival and success.The goal of this workshop is to rethink our frame of reference and use collaborative methods to discover new perspectives in OUT approach to our next communication project. Members of the workshop will use the LafitteD'Arcy Model of Engagement to stimulate creative alternatives.Our focus will be on: 201 0-7803-5709-4/99/$10.00 0 1999 IEEE
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