Tytuł:

Artificial neural networks as a universal tools for data analysis and modeling in epidemiology and pharmacoeconomics

Autor:

Polak, Sebastian

Temat i słowa kluczowe:

artificial neural networks ; pharmacoeconomics ; modeling

Abstrakt:

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.

Miejsce wydania:

Kraków

Stopień studiów:

2 - studia doktoranckie

Dyscyplina:

informatyka medyczna

Instytucja nadająca tytuł:

Wydział Farmaceutyczny

Promotor:

Brandys, Jerzy

Data:

2006

Data wydania:

2005

Typ:

Praca doktorska

Sygnatura:

ZB-102790

Język:

pol

Prawa dostępu:

nieograniczony

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