Exploring the Preprocessing of a Time-Series Healthcare Administrative Dataset on Deep Learning to Improve Prediction

Exploring the Preprocessing of a Time-Series Healthcare Administrative Dataset on Deep Learning to Improve Prediction

Preprocessing methods are important in enhancing prediction performance for time-series administrative data. This study underscores the importance of preprocessing methods by comparing two data representation techniques, that can be used with sliding window techniques for time-series administrative...

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Bibliographic Details
Main Authors: Faezehsadat Shahidi, M. Ethan Macdonald, Dallas Seitz, Rebecca Barry, Geoffrey Messier
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Gated recurrent unit networks
on clinical demand window structure
sliding window
sequence of events and sequence matrix representations
time-series healthcare administrative data
Online Access:https://ieeexplore.ieee.org/document/10807221/
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https://ieeexplore.ieee.org/document/10807221/

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