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A Case-Based Reasoning System for Neonatal Survival and Los Prediction in Neonatal Intensive Care Units: A Development and Validation Study Publisher Pubmed



Kermani F1 ; Zarkesh MR2, 3 ; Vaziri M4 ; Sheikhtaheri A5
Authors
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Authors Affiliations
  1. 1. Health Information Technology Department, School of Allied Medical Sciences, Semnan University of Medical Sciences, Semnan, Iran
  2. 2. Maternal, Fetal and Neonatal Research Center, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Department of Neonatology, Yas Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Independent Researcher, Semnan, Iran
  5. 5. Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

Source: Scientific Reports Published:2023


Abstract

Early prediction of neonates' survival and Length of Stay (LOS) in Neonatal Intensive Care Units (NICU) is effective in decision-making. We developed an intelligent system to predict neonatal survival and LOS using the Case-Based Reasoning” (CBR) method. We developed a web-based CBR system based on K-Nearest Neighborhood (KNN) on 1682 neonates and 17 variables for mortality and 13 variables for LOS and evaluated the system with 336 retrospectively collected data. We implemented the system in a NICU to externally validate the system and evaluate the system prediction acceptability and usability. Our internal validation on the balanced case base showed high accuracy (97.02%), and F-score (0.984) for survival prediction. The root Mean Square Error (RMSE) for LOS was 4.78 days. External validation on the balanced case base indicated high accuracy (98.91%), and F-score (0.993) to predict survival. RMSE for LOS was 3.27 days. Usability evaluation showed that more than half of the issues identified were related to appearance and rated as a low priority to be fixed. Acceptability assessment showed a high acceptance and confidence in responses. The usability score (80.71) indicated high system usability for neonatologists. This system is available at http://neonatalcdss.ir/ . Positive results of our system in terms of performance, acceptability, and usability indicated this system can be used to improve neonatal care. © 2023, The Author(s).
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