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Information Journal Paper

Title

A Rule Based Intelligent Software to Predict Length of Stay and the Mortality Rate in Trauma Patients in the Intensive Care Unit

Pages

  175-183

Abstract

 Background: Intensive Care Unit (ICU) has the highest Mortality rate in the world. ICU has special equipment that leads to the hospital's most costly parts. The Length of stay in the ICU is a special issue, and reducing this time is a practical approach. We aimed to use artificial intelligence to help early and timely diagnosis of the dis-ease to help with health. Methods: We designed a rule-based intelligent system to predict the Length of stay and the Mortality rate of trauma patients in ICU. A neuro-Fuzzy and eight machine learning models were used to predict the Mortality rate in trauma patients in ICU. The performances of these techniques were evaluated with accuracy, sensitivity, specificity, and area under the ROC curve. Decision-Table was used to predict the Length of stay in trauma pa-tients in ICU. For comparison, eight machine learning models were used. The method is compared based on Mean absolute error and relative absolute error (%). Results: Neuro-Fuzzy expert system and Decision-Table showed better results than other techniques. Accura-cy, sensitivity, specificity, and ROC Area of Nero-Fuzzy are 83. 6735, 0. 9744, 0. 3000, 0. 8379, and 1, respective-ly. The mean absolute error and Relative absolute error (%) of the Decision-table model are 4. 5426 and 65. 4391, respectively. Conclusion: Neuro-Fuzzy expert system with the highest level of accuracy and a Decision-Table with the low-est Mean absolute error, which are rule-based models, are the best models. Therefore, these models are rec-ommended as a valuable tool for prediction parameters of ICU as well as medical decision-making.

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    Cite

    APA: Copy

    MONTAZERI, MITRA, AHMADINEJAD, MEHDI, BAHAADINBEIGY, KAMBIZ, Montazeri, Mohadeseh, & AHMADIAN, LEILA. (2023). A Rule Based Intelligent Software to Predict Length of Stay and the Mortality Rate in Trauma Patients in the Intensive Care Unit. IRANIAN JOURNAL OF PUBLIC HEALTH, 52(1), 175-183. SID. https://sid.ir/paper/1099004/en

    Vancouver: Copy

    MONTAZERI MITRA, AHMADINEJAD MEHDI, BAHAADINBEIGY KAMBIZ, Montazeri Mohadeseh, AHMADIAN LEILA. A Rule Based Intelligent Software to Predict Length of Stay and the Mortality Rate in Trauma Patients in the Intensive Care Unit. IRANIAN JOURNAL OF PUBLIC HEALTH[Internet]. 2023;52(1):175-183. Available from: https://sid.ir/paper/1099004/en

    IEEE: Copy

    MITRA MONTAZERI, MEHDI AHMADINEJAD, KAMBIZ BAHAADINBEIGY, Mohadeseh Montazeri, and LEILA AHMADIAN, “A Rule Based Intelligent Software to Predict Length of Stay and the Mortality Rate in Trauma Patients in the Intensive Care Unit,” IRANIAN JOURNAL OF PUBLIC HEALTH, vol. 52, no. 1, pp. 175–183, 2023, [Online]. Available: https://sid.ir/paper/1099004/en

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