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IBA-VNS: A Logic-Based Machine Learning Algorithm and Its Application in Surgery

Author

Listed:
  • Nevena Čolić

    (Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, 11000 Belgrade, Serbia)

  • Pavle Milošević

    (Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, 11000 Belgrade, Serbia)

  • Ivana Dragović

    (Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, 11000 Belgrade, Serbia)

  • Miljan S. Ćeranić

    (Clinic for Emergency Surgery, University Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia)

Abstract

The interpretability and explainability of machine learning (ML) approaches play a key role in the trustworthiness of ML models in various applications. The objective of this paper is to incorporate a logic-based reasoning in the ML model that is not only accurate but also interpretable and easily applied. More precisely, we propose a hybrid IBA-VNS approach based on interpolative Boolean algebra (IBA) and variable neighborhood search (VNS). IBA is chosen over traditional multi-valued and/or fuzzy logic techniques due to its consistency in preserving all Boolean axioms. The VNS heuristic is used for model training, i.e., determining the optimal logical aggregation function within the IBA framework for solving observed prediction problems. Obtained logic aggregation functions are easy to understand and may provide additional insight to the decision-maker. The proposed approach does not require any domain knowledge and is applicable in various domains. IBA-VNS is evaluated on several standard datasets. Further, IBA-VNS is applied to the real-world problem of predicting hospital length of stay (LOS), showing exceptional results in terms of interpretability and accuracy. In fact, the dataset is collected from the LabSerb program regarding colorectal surgeries in the period 2015–2023. The proposed approach extracted knowledge regarding the problem, i.e., the causal relations between the patient’s health condition and LOS, along with achieving an MAE of 1.144 days.

Suggested Citation

  • Nevena Čolić & Pavle Milošević & Ivana Dragović & Miljan S. Ćeranić, 2024. "IBA-VNS: A Logic-Based Machine Learning Algorithm and Its Application in Surgery," Mathematics, MDPI, vol. 12(7), pages 1-21, March.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:7:p:950-:d:1362428
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    References listed on IDEAS

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    1. Pierre Hansen & Nenad Mladenović & José Moreno Pérez, 2010. "Variable neighbourhood search: methods and applications," Annals of Operations Research, Springer, vol. 175(1), pages 367-407, March.
    2. Abraham Duarte & Juan Pantrigo & Eduardo Pardo & Nenad Mladenovic, 2015. "Multi-objective variable neighborhood search: an application to combinatorial optimization problems," Journal of Global Optimization, Springer, vol. 63(3), pages 515-536, November.
    3. Pierre Hansen & Nenad Mladenović & Jack Brimberg & José A. Moreno Pérez, 2019. "Variable Neighborhood Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, edition 3, chapter 0, pages 57-97, Springer.
    4. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    5. Mladenovic, Nenad & Drazic, Milan & Kovacevic-Vujcic, Vera & Cangalovic, Mirjana, 2008. "General variable neighborhood search for the continuous optimization," European Journal of Operational Research, Elsevier, vol. 191(3), pages 753-770, December.
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