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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Khope, Sarika
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Computer Science & IT Engineering

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Hybridized deep learning model with novel recommender for predicting criticality state of patient using MIMIC-IV dataset Khope, Sarika; Kotambkar, Deepali; Adiraju, Rama Vasantha; Battalwar, Smita Suhas
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3926-3933

Abstract

The contribution of machine learning towards prediction of critical state of patient is the prime focus of the current study. The review of current approaches of machine learning has been witnessed with various shortcomings. Hence, the proposed study adopts medical information mart for intensive care (MIMIC-IV) dataset in order to develop a novel analytical model that can predict the criticality state of patient in their next visit. The model has been designed by hybridizing convolution neural network (CNN) and long short-term memory (LSTM) which takes the discrete input of hospital and individual patient information in each visit. The concatenated feature is then subjected to a newly introduced recommender module which offers implicit feedback by assigning a ranking score. The final predictive outcome of study offers criticality rank. The study model is benchmarked with existing machine learning approaches to find 54% of increased accuracy and 70% of reduced processing time.
Co-Authors Adiraju, Rama Vasantha Battalwar, Smita Suhas Kotambkar, Deepali