Torres Parejo Úrsula, Campaña Jesús Roque, Vila María Amparo, Delgado Miguel
Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain.
Department of Computer Science and Artificial Intelligence, University of Granada, 18014 Granada, Spain.
Entropy (Basel). 2021 Sep 29;23(10):1275. doi: 10.3390/e23101275.
Medical records contain many terms that are difficult to process. Our aim in this study is to allow visual exploration of the information in medical databases where texts present a large number of syntactic variations and abbreviations by using an interface that facilitates content identification, navigation, and information retrieval. We propose the use of multi-term tag clouds as content representation tools and as assistants for browsing and querying tasks. The tag cloud generation is achieved by using a novelty mathematical method that allows related terms to remain grouped together within the tags. To evaluate this proposal, we have carried out a survey over a spanish database with 24,481 records. For this purpose, 23 expert users in the medical field were tasked to test the interface and answer some questions in order to evaluate the generated tag clouds properties. In addition, we obtained a precision of 0.990, a recall of 0.870, and a 1-score of 0.904 in the evaluation of the tag cloud as an information retrieval tool. The main contribution of this approach is that we automatically generate a visual interface over the text capable of capturing the semantics of the information and facilitating access to medical records, obtaining a high degree of satisfaction in the evaluation survey.
医疗记录包含许多难以处理的术语。我们在本研究中的目标是，通过使用一个便于内容识别、导航和信息检索的界面，对医学数据库中的信息进行可视化探索，这些数据库中的文本存在大量句法变化和缩写。我们建议使用多词标签云作为内容表示工具以及浏览和查询任务的辅助工具。标签云的生成是通过使用一种新颖的数学方法实现的，该方法允许相关术语在标签中保持分组在一起。为了评估这一建议，我们对一个包含24481条记录的西班牙语数据库进行了一项调查。为此，23名医学领域的专家用户被要求测试该界面并回答一些问题，以便评估生成的标签云属性。此外，在将标签云作为信息检索工具进行评估时，我们获得了0.990的精确率、0.870的召回率和0.904的F1分数。这种方法的主要贡献在于，我们能够在文本之上自动生成一个可视化界面，该界面能够捕捉信息的语义并便于访问医疗记录，在评估调查中获得了高度满意度。
