MIMIC III and its contribution to critical care prediction models

Το τεκμήριο παρέχεται από τον φορέα :
Πανεπιστήμιο Δυτικής Αττικής (ΠΑ.Δ.Α.)   

Αποθετήριο :
Journal of Integrated Information Management  | ΕΚΤ eJournals   

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MIMIC III and its contribution to critical care prediction models (EN)

Markopoulos, Dimitrios
Tsolakidis, Anastasios
Skourlas, Christos

info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article (EN)

2024-05-26


Purpose - The present paper attempts to present the research that has been made on prediction models using deep learning methods with data retrieved from mimic III database and to identify challenges and possible areas for future research. Methodology - A literature research was conducted for articles related to MIMIC III and prediction models related to the database published from 2016 to 2021. Also, reviews and papers related to neural networks, machine learning, data mining and implementation and usage of electronic health records (EHR) in ICU were investigated to support findings from mimic III papers. Findings - Prediction algorithms can be very useful in ICU units. Although some algorithms, such as InSight are specialized in specific diseases, others such as XGBOOST and recurrent neural networks can be used in a broader area, presenting quite accurate results. Originality - Usually, reviews categorize research on MIMIC database per disease or per the desired outcome, such as the prediction of length of stay and the final outcome. The current study categorizes the research based on the tools, prediction models, and algorithms used. This way, it is possible to understand better how each method performs to various conditions and desired outcomes. (EN)


prediction models (EN)
Intensive Care Units (EN)
neural networks (EN)
MIMIC III (EN)
random forests (EN)
big data (EN)

Αγγλική γλώσσα

Τμήμα Αρχειονομίας, Βιβλιοθηκονομίας & Συστημάτων Πληροφόρησης, Σχολή Διοικητικών, Οικονομικών & Κοινωνικών Επιστημών, Πανεπιστήμιο Δυτικής Αττικής (EN)


2623-4629
Journal of Integrated Information Management; Vol. 6 No. 2 (2021): Jul-Dec 2021; 7-12 (EN)

https://creativecommons.org/licenses/by-nc/4.0




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