The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021)

被引:2
|
作者
Adhikari, Bijaya [1 ]
Srivastava, Ajitesh [2 ]
Pei, Sen [3 ]
Kefayati, Sarah [4 ]
Yu, Rose [5 ]
Yadav, Amulya [6 ]
Rodriguez, Alexander [7 ]
Ramanathan, Arvind [8 ]
Vullikanti, Anil [9 ]
Prakash, B. Aditya [7 ]
机构
[1] Univ Iowa, Iowa City, IA 52242 USA
[2] Univ Southern Calif, Los Angeles, CA 90007 USA
[3] Columbia Univ, New York, NY 10027 USA
[4] IBM Corp, Seattle, WA USA
[5] Univ Calif San Diego, La Jolla, CA 92093 USA
[6] Penn State Univ, University Pk, PA 16802 USA
[7] Georgia Inst Technol, Atlanta, GA 30332 USA
[8] Argonne Natl Lab, Argonne, IL 60439 USA
[9] Univ Virginia, Charlottesville, VA 22903 USA
关键词
epidemiology; public health; forecasting; AI for good;
D O I
10.1145/3447548.3469475
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The 4th epiDAMIK@SIGKDD workshop is a forum to discuss new insights into how data mining can play a bigger role in epidemiology and public health research. While the integration of data science methods into epidemiology has significant potential, it remains under studied. We aim to raise the profile of this emerging research area of data-driven and computational epidemiology, and create a venue for presenting state-of-the-art and in-progress results-in particular, results that would otherwise be difficult to present at a major data mining conference, including lessons learnt in the 'trenches'. The current COVID-19 pandemic has only showcased the urgency and importance of this area. Our target audience consists of data mining and machine learning researchers from both academia and industry who are interested in epidemiological and public-health applications of their work, and practitioners from the areas of mathematical epidemiology and public health.
引用
收藏
页码:4104 / 4105
页数:2
相关论文
共 30 条