A prognosis system for colorectal cancer

Tiago Oliveira, E. Barbosa, Sandra F. Martins, A. Goulart, J. Neves, P. Novais
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引用次数: 6

Abstract

The level of uncertainty and incompleteness in the information upon which healthcare professionals have to make judgments has been a subject of discussion in the past, and more nowadays, with the advent of the so-called Clinical Decision Support Systems. This work addresses uncertainty in the postoperative prognosis for colorectal cancer. The interdependence and synergistic effect of different clinical features comes into play when it is necessary to predict how a patient will react to this type of surgery. Using a probabilistic based knowledge representation, a decision support system was conceived in order to provide support for physicians under these circumstances, in particular to surgeons. The solution proposed is based on machine learning on records of cancer patients, incorporating explicit knowledge of experts about the domain. To facilitate access and thus increase its dissemination in the healthcare community, the system is integrated in a wider platform available through a web application.
结直肠癌的预后系统
在过去,医疗保健专业人员必须做出判断的信息的不确定性和不完整性一直是讨论的主题,而现在,随着所谓的临床决策支持系统的出现,讨论的主题更多。这项工作解决了结直肠癌术后预后的不确定性。当需要预测患者对这类手术的反应时,不同临床特征的相互依赖和协同作用就会发挥作用。利用基于概率的知识表示,设想了一个决策支持系统,以便在这些情况下为医生,特别是外科医生提供支持。提出的解决方案是基于癌症患者记录的机器学习,结合专家对该领域的明确知识。为方便市民取用及在医疗界推广该系统,系统已整合在一个更广泛的平台内,可透过网页应用程式使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
3.10
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