| Title |
Overview of the artificial intelligence methods and analysis of their application potential / |
| Authors |
Krikščiūnienė, Dalia ; Sakalauskas, Virgilijus |
| DOI |
10.1007/978-3-030-79353-1_9 |
| ISBN |
9783030793524 |
| eISBN |
9783030793531 |
| Full Text |
|
| Is Part of |
Intelligent systems for sustainable person-centered healthcare : [collective monograph] / editors: Dalia Kriksciuniene, Virgilijus Sakalauskas.. Cham : Springer, 2022. p. 167-183.. ISBN 9783030793524. eISBN 9783030793531 |
| Keywords [eng] |
artificial intelligence ; data mining ; healthcare data ; machine learning algorithms |
| Abstract [eng] |
The medical industry collects a huge amount of data, most of which is electronic health records. These data cannot be processed and analyzed using traditional statistical or data analysis methods because of the complexity and a volume of the data. So the knowledge discovery from raw clinical data is a big challenge for healthcare system. In this chapter we introduce the issue of data mining in healthcare, i.e. how to use the raw clinical data to ensure a systematic approach to health problems, highlight good practices, reveal inefficiencies, and improve healthcare efficiency. We identify the data sources used in healthcare, discuss its adequacy, interpretation, transformation and cleansing challenges. Also we consider the variety characteristics and specific capacities of methods, applied in the areas of data mining. Particular attention is paid to the diversity of Machine Learning and Artificial intelligence methods, analytical health data analysis models, its testing and evaluation capabilities. |
| Published |
Cham : Springer, 2022 |
| Type |
Book part |
| Language |
English |
| Publication date |
2022 |
| CC license |
|
