Markopoulos, DimitriosTsolakidis, AnastasiosSkourlas, ChristosPurpose - 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.application/pdfhttps://ejournals.epublishing.ekt.gr/index.php/jiim/article/view/37890engΤμήμα Αρχειονομίας, Βιβλιοθηκονομίας & Συστημάτων Πληροφόρησης, Σχολή Διοικητικών, Οικονομικών & Κοινωνικών Επιστημών, Πανεπιστήμιο Δυτικής Αττικήςhttps://creativecommons.org/licenses/by-nc/4.02623-4629Journal of Integrated Information Management; Vol. 6 No. 2 (2021): Jul-Dec 2021; 7-12prediction modelsIntensive Care Unitsneural networksMIMIC IIIrandom forestsbig dataMIMIC III and its contribution to critical care prediction modelsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Article2024-05-26Δημοσίευση σε περιοδικόPublication in journalΕπιστήμη πληροφόρησηςInformation scienceisi - Information Science & Library Science covers resources on a wide variety of topics, including bibliographic studies, cataloguing, categorization, database construction and maintenance, electronic libraries, information ethics, information processing and management, interlending, preservation, scientometrics, serials librarianship, and special libraries.Διοικητική Επιστήμη και Επιχειρησιακή ΈρευναManagement Science and Operations Researchisi - Operations Research & Management Science includes resources on the definition, analysis, and solution of complex problems. Relevant topics in this category include mathematical modeling, stochastic modeling, decision theory and systems, optimization theory, logistics, and control theory.Επιστημονικό άρθροScientific articleΠανεπιστήμιο Δυτικής Αττικής (ΠΑ.Δ.Α.)Greek Aggregator OpenArchives.gr | National Documentation Centre (EKT)