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Author:Dong, Siyuan
Title:A time dependent adaptive learning process for estimating drug exposure from register data - applied to insulin and its analogues
Publication type:Master's thesis
Publication year:2013
Pages:[5] + 54      Language:   eng
Department/School:Perustieteiden korkeakoulu
Main subject:Tietojenkäsittelyteoria   (T-79)
Supervisor:Aurell, Erik ; Gräslund, Torbjörn
Instructor:Hoti, Fabian J.
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark Aalto     | Archive
Keywords:insulin daily dosage
time dependent
adaptive learning process
prospective method
Abstract (eng): In register based drug research time dependent drug exposure is evaluated based on information available from the prescription register.
In Finland the exact daily dosage information is not available and thus has to be estimated from the total amount purchased and the purchase patterns.

The aim of this master thesis project is to develop a new algorithm, named Time Dependent Adaptive Learning Process (TDALP), which is a prospective method and applies the historical records to estimate the current insulin daily dosage.

Through testing under different situations including both constant daily dosage cases and alterable daily dosage cases, it is demonstrated that the performance of the new algorithm is superior over the more traditional methods.
ED:2013-09-25
INSSI record number: 47248
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