As society develops, the number of published research articles raises. Besides, the pressure to publish has been increased because the competitiveness between researchers working on similar topics. Although this increment is desirable, it leads to multiple issues. At a reader level, insurmountable barriers to keep up with the state of the art appear. From a publisher perspective, it is a very demanding task to determine which research articles are worth publishing. Automatizing these tasks appears as a core solution. In the case of readers, a previous evaluation of articles would simplify the filtering process. As for publishers, they could perform preliminary selections or estimate the reviewing effort. This paper presents Medical Evaluator System for Scientific Interoperability (MESSI) system to overcome all these issues. It is able to evaluate the novelty and reliability of health-related texts. The novelty calculation is based on previously acquired knowledge after processing more than 500,000 papers. The reliability estimation is based on the reputations of similar articles calculated based on previously defined metrics. Multiple experiments have been addressed to illustrate the viability of the proposal. The obtained results show a good performance that encourage to continue evolving the system.

随着社会的发展，发表的研究论文的数量也在增加。此外，由于从事类似主题的研究人员之间的竞争，发表的压力也增加了。尽管这种增量是可取的，但它会导致多个问题。在读者层面，出现了跟上最先进技术的不可逾越的障碍。从出版商的角度来看，确定哪些研究文章值得发表是一项非常艰巨的任务。自动化这些任务似乎是一个核心解决方案。就读者而言，之前对文章的评估将简化过滤过程。至于出版商，他们可以进行初步选择或估计审查工作。本文介绍了用于科学互操作性的医学评估系统( MESSI)) 系统来克服所有这些问题。它能够评估与健康相关的文本的新颖性和可靠性。新颖性计算基于先前在处理超过 500,000 篇论文后获得的知识。可靠性估计基于根据先前定义的指标计算的类似文章的声誉。已经进行了多次实验以说明该提案的可行性。获得的结果显示出良好的性能，鼓励继续发展系统。