Using Knowledge Discovery in Database & Data Mining to Develop Techniques in Medical Informatics Applied to Surgical Databases
在数据库中使用知识发现
基本信息
- 批准号:9803782
- 负责人:
- 金额:$ 6.47万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:1998
- 资助国家:美国
- 起止时间:1998-06-01 至 2000-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The tools used in the field of medical informatics are those of knowledge discovery in databases (KDD) or alternatively, data mining. KDD spans a variety of fields: statistics, pattern recognition, artificial intelligence, and data warehousing. However, it has become a distinct discipline with its own objectives. The purpose of data mining is to extract previously unknown and potentially useful information. KDD differs from the more traditional statistical tools by focusing on model identification while minimizing misclassification. Statistical methods tend to focus on estimation and model identification. The hypotheses generated by the KDD process must then be validated by standard statistical techniques. It has become increasingly clear that more traditional techniques are not adequate because of the size and complexity of the databases. One 450-bed hospital maintained a database with six months of laboratory tests and medications as well as summaries of patient followup for 15 months. The storage capacity of the computer had to be increased by 12 gigabytes. The dependence upon an investigator examining relationships in the data must yield to an automated process. KDD can generate interesting and unexpected hypotheses which can be examined by statistical methods. The automatic hypothesis formation and testing cycle can continue until important patterns emerge. This project involves the study and development of data mining techniques applied to several databases primarily stored in the Alliant Health System. This includes a database containing a 25-year followup on a cohort of 10,000 women in Kentucky to examine patterns of health and lifestyle. In addition, the techniques will be applied to a database of student information to examine relationships between student habits, student success, and student learning. Using the developed materials and databases, a course will be taught to students in the Department of Mathematics on applications of data mining. This GOALI project is jointly supported by the MPS Office of Multidisciplinary Activities (OMA) and the Division of Mathematical Sciences (DMS).
医学信息学领域使用的工具是数据库中的知识发现(KDD)或数据挖掘。KDD跨越了许多领域:统计学、模式识别、人工智能和数据仓库。 然而,它已经成为一个独特的学科,有自己的目标。数据挖掘的目的是提取以前未知的和潜在有用的信息。KDD与传统的统计工具不同,它侧重于模型 识别,同时最大限度地减少错误分类。统计方法往往侧重于估计和模型识别。KDD过程产生的假设必须通过标准的统计技术进行验证。 越来越明显的是,由于数据库的规模和复杂性,较传统的技术是不够的。一家拥有450张床位的医院维护了一个数据库,其中包括6个月的实验室检查和药物治疗以及15个月的患者随访摘要。计算机的存储容量必须增加12千兆字节。依赖于调查人员检查数据中的关系必须屈服于自动化过程。KDD可以产生有趣的和意想不到的假设,可以通过统计方法进行检验。自动的假设形成和测试循环可以继续,直到重要的模式出现。 该项目涉及研究和开发数据挖掘技术,应用于主要储存在Alliant保健系统中的几个数据库。这包括一个数据库,其中包含对肯塔基州1万名妇女进行的25年随访,以检查健康和生活方式的模式。 此外,这些技术将应用于学生信息数据库,以检查学生习惯,学生成功和学生学习之间的关系。利用开发的材料和数据库,将向数学系的学生教授一门关于数据挖掘应用的课程。 该GOALI项目由MPS多学科活动办公室(OMA)和数学科学部(DMS)联合支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Patricia Cerrito其他文献
Patricia Cerrito的其他文献
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{{ truncateString('Patricia Cerrito', 18)}}的其他基金
Data Mining and Geographic Information Systems (GIS) to Investigate Public Health Information
用于调查公共卫生信息的数据挖掘和地理信息系统 (GIS)
- 批准号:
0327581 - 财政年份:2003
- 资助金额:
$ 6.47万 - 项目类别:
Standard Grant
Data Mining and GIS Spatial Analysis to Study Epidemiological Trends in Asthma
数据挖掘和 GIS 空间分析研究哮喘流行病学趋势
- 批准号:
0106315 - 财政年份:2001
- 资助金额:
$ 6.47万 - 项目类别:
Standard Grant
MP/PPD: Teaching of Mathematics for Students with Attention Deficit Disorder
MP/PPD:注意力缺陷障碍学生的数学教学
- 批准号:
9550452 - 财政年份:1995
- 资助金额:
$ 6.47万 - 项目类别:
Standard Grant
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