Using Text Mining to Aid Cancer Risk Assessment

大量的证据表明，环境和职业对癌症的贡献证明，迫切需要加快政策努力，以防止致癌暴露。如果不采取这种预防行动，公众健康和环境的保护就会受到威胁。充分的风险管理取决于可靠的风险评估。风险评估涉及评价现有的科学知识，以确定接触某种物质与因接触该物质而患癌症的可能性之间的关系。由此产生的评估确定哪些物质与患癌症的高风险有关，哪些物质几乎没有风险。它们为当局提供了制定环境污染物接触限值的决策所需的关键材料。人工进行的风险评估是一项具有挑战性和耗时的任务，需要将科学专业知识与详细的文献检索和审查相结合。单一致癌物风险评估所需的数据可能分散在数千篇期刊文章中。随着文献的指数增长，分子生物学技术的快速发展，以及对影响癌症发展的机制的了解越来越多，这项任务变得过于雄心勃勃，无法通过手动方式管理，我们建议开发一个实用的工具，能够帮助风险评估人员在他们的工作。该工具利用了计算机科学中的文本挖掘技术。文本挖掘旨在从书面资源中自动提取和发现新的信息。它可用于支持风险评估的各个步骤，包括查找与风险评估相关的期刊文章，查找文章中的相关信息，以及确定和收集与化学品特定致癌特性相关的信息。文本挖掘所需的基本技术现在已经可用，但这些技术需要针对实际任务进行定制和扩展。在这个项目中，我们将修改现有的和开发新的文本挖掘技术的癌症风险评估的需要。我们将把最好的技术整合成一个实用的工具，供风险评估人员在工作中使用。我们希望该工具可以极大地帮助风险评估人员管理大型文本数据，提高他们的工作效率，并帮助知识发现。

The amount of evidence regarding environmental and occupational contributions to cancer justifies urgent acceleration of policy efforts to prevent carcinogenic exposures. Without such precautionary actions the protection of public health and the environment is at risk. Adequate risk management is dependent on reliable risk assessment. Risk assessment involves evaluating existing scientific knowledge to establish the relationship between exposure to a substance and the likelihood of developing cancer from that exposure. The resulting assessments determine which substances are associated with high risks of developing cancer and which carry little or no risk. They provide the authorities with the key material needed for making decisions on setting exposure limits on environmental contaminants.Performed manually, risk assessment is a challenging and time-consuming task which requires combining scientific expertise with elaborate literature search and review. Data required for risk assessment of a single carcinogen may be scattered across thousands of journal articles. With the exponentially growing body of literature, the rapid development of molecular biology techniques, and the increasing knowledge of mechanisms affecting cancer development, the task is getting too ambitious to manage via manual means.We propose to develop a practical tool capable of assisting risk assessors in their work. This tool makes use of text mining technology from computer science. Text mining is aimed at automatically extracting and discovering novel information from written resources. It could be used to support various steps of risk assessment, including finding the journal articles relevant for risk assessment, locating the relevant information in the articles, and identifying and gathering the information related to the specific carcinogenic properties of chemicals. The basic techniques required for text mining are now available, but these techniques need to be tailored and extended for real-world tasks. In this project we will modify existing and develop novel text mining technology for the needs of cancer risk assessment. We will integrate the best of the resulting technology into a practical tool which risk assessors can use in their work. Our hope is that the tool can greatly assist risk assessors with the management of large textual data, increase their productivity, and aid knowledge discovery.