Alialy Roshanak, Tavakkol Sasan, Tavakkol Elham, Ghorbani-Aghbologhi Amir, Ghaffarieh Alireza, Kim Seon Ho, Shahabi Cyrus
Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
Department of Computer Science, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
J Pathol Inform. 2018 Feb 14;9:2. doi: 10.4103/jpi.jpi_65_17. eCollection 2018.
The advent of the digital pathology has introduced new avenues of diagnostic medicine. Among them, crowdsourcing has attracted researchers' attention in the recent years, allowing them to engage thousands of untrained individuals in research and diagnosis. While there exist several articles in this regard, prior works have not collectively documented them. We, therefore, aim to review the applications of crowdsourcing in human pathology in a semi-systematic manner. We first, introduce a novel method to do a systematic search of the literature. Utilizing this method, we, then, collect hundreds of articles and screen them against a predefined set of criteria. Furthermore, we crowdsource part of the screening process, to examine another potential application of crowdsourcing. Finally, we review the selected articles and characterize the prior uses of crowdsourcing in pathology.
数字病理学的出现为诊断医学开辟了新途径。其中，众包近年来吸引了研究人员的关注，使他们能够让数千名未经培训的人员参与研究和诊断。虽然在这方面已有多篇文章，但之前的研究并未对其进行全面记录。因此，我们旨在以半系统的方式回顾众包在人体病理学中的应用。我们首先介绍一种对文献进行系统检索的新方法。利用这种方法，我们收集了数百篇文章，并根据一组预定义的标准对其进行筛选。此外，我们将部分筛选过程众包出去，以检验众包的另一个潜在应用。最后，我们回顾所选文章，并描述众包在病理学中的先前应用情况。
