A fuzzy ontology-based case-based reasoning system for stomach dystemperament in Persian medicine

PLOS ONE RESEARCH ARTICLE A fuzzy ontology-based case-based reasoning system for stomach dystemperament in Persian medicine Hassan Shojaee-Mend ID1, Haleh Ayatollahi ID2*, Azam Abdolahadi3 1 Infectious Diseases Research Center, Gonabad University of Medical Sciences, Gonabad, Iran, 2 Health Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran, 3 Department of Complementary Medicine, Research Institute for Islamic and Complementary Medicine, Iran University of Medical Sciences, Tehran, Iran a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 * Abstract Background OPEN ACCESS Citation: Shojaee-Mend H, Ayatollahi H, Abdolahadi A (2024) A fuzzy ontology-based casebased reasoning system for stomach dystemperament in Persian medicine. PLoS ONE 19(10): e0309722. https://doi.org/10.1371/journal. pone.0309722 Editor: Agnieszka Konys, West Pomeranian University of Technology, POLAND Received: March 7, 2024 Accepted: August 16, 2024 Published: October 24, 2024 Copyright: © 2024 Shojaee-Mend et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All codes and data are available on GitHub at https://github.com/ shojaee/CBR-Dystemperament. Funding: that this study was financially supported by Iran University of Medical Sciences (IUMS/ SHMIS_97-3-37-12671). However, the funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. I am looking forward to hearing from you. Thank you. In Persian medicine, early diagnosis and treatment of stomach dystemperament is crucial for preventing other diseases. However, traditional medicine diagnosis often involves ambiguous and less structured information making it challenging for practitioners. Integrating fuzzy ontology with case-based reasoning (CBR) systems can enhance diagnostic accuracy in this filed. Objectives This study aimed to develop and evaluate a fuzzy ontology-based CBR system for diagnosing and treating stomach dystemperament in Persian medicine. Methods This was a mixed-methods research in which a fuzzy ontology-based CBR system was developed based on the fuzzy features, utilizing trapezoidal, triangular, right shoulder and left shoulder membership functions to represent linguistic variables such as hunger level and digestion power. The research phases included identifying relevant terms, concepts, and relationships, developing the fuzzy case-base ontology using the IKARUS-Onto methodology, and subsequently designing and implementing the CBR system. The system performance was evaluated in terms of its sensitivity, specificity, accuracy, precision, and F1score. Results Initially, a case-base fuzzy ontology was created. Then, the database was built up using 88 expert-validated medical records. Of these cases, 72% (63 cases) were diagnosed with phlegmatic dystemperament, 18% (16 cases) with cold-dry dystemperament, and 10% (9 cases) had no stomach dystemperament. The CBR system was developed and evaluated PLOS ONE | https://doi.org/10.1371/journal.pone.0309722 October 24, 2024 1 / 15 PLOS ONE Competing interests: The authors have declared that no competing interests exist. A fuzzy ontology-based CBR system for stomach dystemperament in Persian medicine using sensitivity, specificity, accuracy, precision, and F1-score which were 97.5%, 87.5%, 96.6%, 98.7%, and 98.1%, respectively. Conclusions Our fuzzy ontology-based CBR demonstrated high performance in diagnosing stomach dystemperament in Persian medicine. This system shows promise in improving diagnostic accuracy and facilitating the identification of similar cases. While initial results are encouraging, further evaluation in a real clinical environment is recommended to fully assess its practical utility. Introduction Traditional medicine encompasses practices rooted in indigenous cultures worldwide, and has long been used to maintain health and treat illnesses [1]. The World Health Organization (WHO) accepted this specialty and emphasized its accessibility and cost-effectiveness [1, 2]. Persian medicine with a history spanning over 1000 years, is one of the oldest types of traditional medicine [3]. In Persian medicine, the digestive system, particularly the stomach, holds great significance due to its perceived connection with other bodily organs. Many diseases are believed to be related to digestive system disturbances, especially improper stomach function [4, 5]. Consequently, early diagnosis and treatment of stomach dystemperament is considered crucial for preventing various diseases [6]. However, traditional medicine, including Persian medicine, faces several challenges. Diagnosis often relies heavily on the physician’s experience, and information is not always welldocumented or standardized [7, 8]. Moreover, in traditional medicine, clinical data often relies on qualitative descriptions and subjective symptoms rather than quantitative measurements. This is particularly evident in diagnosing stomach dystemperament, where most indicators are subjective and expressed in natural language. [5] These factors make collecting domain-specific data challenging and highlight the potential value of experience in supporting clinical decisions [9]. Case-based reasoning (CBR) is a technology that has shown promises in various medical fields, but has received less attention in traditional medicine [10–12]. CBR systems can enhance decision-making quality and reduce medical errors [8]. However, designing such systems for traditional medicine is challenging due to the unstructured nature of clinical information and the lack of well-described specialized knowledge [13]. To address these challenges, the development and use of medical ontology as the foundation for CBR systems can be highly beneficial [14]. Medical ontology provides background knowledge and facilitates semantic retrieval, which becomes increasingly important as the number of cases grows [15]. Furthermore, fuzzy ontology can accommodate the ambiguous knowledge often present in traditional medicine [16]. While several CBR systems have been introduced in traditional Chinese medicine [17, 18], limited research has been conducted on Persian medicine ontology and CBR system development [19, 20]. Given that Persian medicine knowledge is largely experience-based and involves ambiguity, developing clinical decision support systems such as CBRs, supported by fuzzy ontology, could enhance the efficiency of Persian medicine specialists in diagnosing diseases. This study aimed to address the following research question: How can we develop a fuzzy ontology-based CBR system to support the diagnosis and treatment of stomach PLOS ONE | https://doi.org/10.1371/journal.po (...truncated)