Object
Title: Artificial neural networks as a universal tools for data analysis and modeling in epidemiology and pharmacoeconomics
Abstract:
he aim of the project is to verify potentia! artificial neural networks application as universal data analysis tools m epidemiology and pharmacoeconomics. Artificial neural networks are numbered among computational intelligence systems. Substantial difference between classical computational machines and those built on the neural paradigm is the latter ability to parallel processmg by set of independent units performing simple opera-tions (summation, function transformation). Redundancy and parallelism of computations are implicating -basic advantages of artificial neural net-works m comparison to classical computers like: robustness for the noise in the data, the ability for adaptation, self-organization. Primarily drug assessment was delimited only to its effectiveness. Nowadays pharmacoeconomics is a third part of drug therapy assessment after effectiveness and safety. Information used for exemplary prediction system construction comes from previous pharmacoeconomics analysis of Non-Small Cell Lung Cancer chemotherapy executed in Pharmacoepidemiology and Pharmacoeconomics Department. Depiction of using neural techniques in large, epidemiological datasets analysis is enabled by use of databases from National Center for Health Statistics (NCHS), Center for Disease Control and Prevention (CDC). Obtained results proofs that mentioned above assessmen ; ts.
Place of publishing:
Level of degree:
Degree discipline:
Degree grantor:
Promoter:
Date issued:
Identifier:
Call number:
Language:
Access rights:
Object collections:
Last modified:
Jun 26, 2023
In our library since:
Nov 21, 2012
Number of object content hits:
834
Number of object content views in PDF format
138
All available object's versions:
http://dl.cm-uj.krakow.pl:8080/publication/1247
Show description in RDF format:
Show description in OAI-PMH format:
| Edition name | Date |
|---|---|
| ZB-102790 | Jun 26, 2023 |
Objects
Similar
Polak, Sebastian
Szaleniec, Joanna
Mendyk, Aleksander
Tyrak, Katarzyna
Treliński, Michał
