Public Health and Epidemiology Informatics

Author:

Bar-Hen A.,Paragios N.,Flahault A.

Abstract

Summary Objectives: The aim of this manuscript is to provide a brief overview of the scientific challenges that should be addressed in order to unlock the full potential of using data from a general point of view, as well as to present some ideas that could help answer specific needs for data understanding in the field of health sciences and epidemiology. Methods: A survey of uses and challenges of big data analyses for medicine and public health was conducted. The first part of the paper focuses on big data techniques, algorithms, and statistical approaches to identify patterns in data. The second part describes some cutting-edge applications of analyses and predictive modeling in public health. Results: In recent years, we witnessed a revolution regarding the nature, collection, and availability of data in general. This was especially striking in the health sector and particularly in the field of epidemiology. Data derives from a large variety of sources, e.g. clinical settings, billing claims, care scheduling, drug usage, web based search queries, and Tweets. Conclusion: The exploitation of the information (data mining, artificial intelligence) relevant to these data has become one of the most promising as well challenging tasks from societal and scientific viewpoints in order to leverage the information available and making public health more efficient.

Publisher

Georg Thieme Verlag KG

Subject

General Medicine

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Artificial Intelligence in Epidemiology;Artificial Intelligence in Medicine;2022

2. Artificial Intelligence in Epidemiology;Artificial Intelligence in Medicine;2021

3. Precision, Equity, and Public Health and Epidemiology Informatics – A Scoping Review;Yearbook of Medical Informatics;2020-08

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