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نتیجه جستجو - data literacy

تعداد مقالات یافته شده: 2
ردیف عنوان نوع
1 Artificial intelligence and machine learning | applications in musculoskeletal physiotherapy
هوش مصنوعی و یادگیری ماشین | برنامه های کاربردی در فیزیوتراپی عضلانی اسکلتی-2019
Introduction: Artificial intelligence (AI) is a field of mathematical engineering which has potential to enhance healthcare through new care delivery strategies, informed decision making and facilitation of patient engagement. Machine learning (ML) is a form of narrow artificial intelligence which can be used to automate decision making and make predictions based upon patient data. Purpose: This review outlines key applications of supervised and unsupervised machine learning in musculoskeletal medicine; such as diagnostic imaging, patient measurement data, and clinical decision support. The current literature base is examined to identify areas where ML performs equal to or more accurately than human levels. Implications: Potential is apparent for intelligent machines to enhance various areas of physiotherapy practice through automization of tasks which involve data analysis, classification and prediction. Changes to service provision through applications of ML, should encourage physiotherapists to increase their awareness of and experiences with emerging technologies. Data literacy should be a component of professional development plans to assist physiotherapists in the application of ML and the preparation of information technology systems to use these techniques.
Keywords: Artificial intelligence | Machine learning | Low back pain | Physiotherapy
مقاله انگلیسی
2 Data infrastructure literacy
سواد اطلاعاتی زیرساخت داده-2018
A recent report from the UN makes the case for ‘‘global data literacy’’ in order to realise the opportunities afforded by the ‘‘data revolution’’. Here and in many other contexts, data literacy is characterised in terms of a combination of numerical, statistical and technical capacities. In this article, we argue for an expansion of the concept to include not just competencies in reading and working with datasets but also the ability to account for, intervene around and participate in the wider socio-technical infrastructures through which data is created, stored and analysed – which we call ‘‘data infrastructure literacy’’. We illustrate this notion with examples of ‘‘inventive data practice’’ from previous and ongoing research on open data, online platforms, data journalism and data activism. Drawing on these perspectives, we argue that data literacy initiatives might cultivate sensibilities not only for data science but also for data sociology, data politics as well as wider public engagement with digital data infrastructures. The proposed notion of data infrastructure literacy is intended to make space for collective inquiry, experimentation, imagination and intervention around data in educational programmes and beyond, including how data infrastructures can be challenged, contested, reshaped and repurposed to align with interests and publics other than those originally intended.
Keywords: Data infrastructures | information infrastructure studies | science and technology studies | digital methods | data activism | data literacy | data publics | data journalism | critical data studies | data critique | data worlds
مقاله انگلیسی
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