A conversational recommender system for diagnosis using fuzzy rules

 

Abstract

Graded implications in the framework of Fuzzy Formal Concept Analysis are used as the knowledge guiding the recommendations. An automated engine based on fuzzy Simplification Logic is proposed to make the suggestions to the users. Conversational recommender systems have proven to be a good approach in telemedicine, building a dialogue between the user and the recommender based on user preferences provided at each step of the conversation. Here, we propose a conversational recommender system for medical diagnosis using fuzzy logic. Specifically, fuzzy implications in the framework of Formal Concept Analysis are used to store the knowledge about symptoms and diseases and Fuzzy Simplification Logic is selected as an appropriate engine to guide the conversation to a final diagnosis. The recommender system has been used to provide differential diagnosis between schizophrenia and schizoaffective and bipolar disorders. In addition, we have enriched the conversational strategy with two strategies (namely critiquing and elicitation mechanism) for a better understanding of the knowledge-driven conversation, allowing user’s feedback in each step of the conversation and improving the performance of the method.

Funding

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Citation

Please, cite this work as:

[Cor+20] P. Cordero, M. Enciso, D. López, et al. “A conversational recommender system for diagnosis using fuzzy rules”. In: Expert Systems with Applications 154 (2020), p. 113449.

NoteBibTeX

@article{cordero2020,
     title={A conversational recommender system for diagnosis using fuzzy rules},
     author={Cordero, Pablo and Enciso, Manuel and López, D and Mora, Angel},
     journal={Expert Systems with Applications},
     volume={154},
     pages={113449},
     year={2020},
     publisher={Elsevier}
}

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A conversational recommender system for diagnosis using fuzzy rules

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Papers citing this work

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1. Domingo López-Rodríguez, Manuel Ojeda-Hernández, Carlos Bejines (2025). New Simplification Rules for Databases with Positive and Negative Attributes. Mathematics DOI
2. Yiwen Zhang, Xiao‐Lan Cao, Wangjian Li, et al. (2025). A fine-grained course session recommendation method based on knowledge point pruning. Scientific Reports DOI
3. Domingo López-Rodríguez, Manuel Ojeda-Hernández, Ángel Mora, et al. (2025). Close-by-One-like algorithms in the fuzzy setting: Theory and experimentation. Fuzzy Sets and Systems DOI
4. Francisco J. Valverde-Albacete, Carmen Peláez-Moreno, Inma P. Cabrera, et al. (2025). Formal Context Transforms and Their Affordances for Exploratory Data Analysis. Mathematics DOI
5. Mathias Uta, Alexander Felfernig, Viet-Man Le, et al. (2024). Knowledge-based recommender systems: overview and research directions. Frontiers in Big Data DOI
6. Qian Hu, Jun Zhang, Jusheng Mi, et al. (2024). TIEOD: Three-way concept-based information entropy for outlier detection. Applied Soft Computing DOI
7. Ľubomír Antoni, Peter Eliaš, Ján Guniš, et al. (2024). Bimorphisms and attribute implications in heterogeneous formal contexts. International Journal of Approximate Reasoning DOI
8. Chang Liu, Dezhong Peng, Hongmei Chen, et al. (2024). Attribute granules-based object entropy for outlier detection in nominal data. Engineering Applications of Artificial Intelligence DOI
9. Rodrigo Couto Santos, Rafael Barea, Arthur Carniato Sanches, et al. (2024). Fuzzy inference algorithm for quantifying thermal comfort in peri-urban environments. Environment Development and Sustainability DOI
10. Manuel Ojeda-Hernández, Domingo López-Rodríguez, Ángel Mora (2024). A Formal Concept Analysis approach to hierarchical description of malware threats. Forensic Science International Digital Investigation DOI
11. Ján Guniš, Ľubomír Šnajder, Ľubomír Antoni, et al. (2024). Formal Concept Analysis of Students’ Solutions on Computational Thinking Game. IEEE Transactions on Education DOI
12. Jun Zhang, Qian Hu, Jusheng Mi, et al. (2024). Hesitant fuzzy three-way concept lattice and its attribute reduction. Applied Intelligence DOI
13. Pushpendu Kar, Monideepa Roy, Sujoy Datta (2024). Some Novel Applications of Recommender System and Road Ahead. Transactions on computer systems and networks DOI
14. Pavol Sokol, Ľubomír Antoni, Ondrej Krídlo, et al. (2023). Formal concept analysis approach to understand digital evidence relationships. International Journal of Approximate Reasoning DOI
15. Sulan Zhang, Jifu Zhang, Jianeng Li, et al. (2023). A user-guided reduction concept lattice and its algebraic structure. Expert Systems with Applications DOI
16. Nagendar Yamsani, M. Sasikala, A. Radhika, et al. (2023). Recommendation System Based on Sparrow Search Optimization Algorithm. DOI
17. Abhishek Kumar Sinha, S. Gopal Krishna Patro, Amrutashree Hota (2023). E-Commerce. Advances in computational intelligence and robotics book series DOI
18. R Damodharan, Madhu mitha S, B Nandhini, et al. (2023). Cognitive Conversational Agent in Healthcare. SSRN Electronic Journal DOI
19. Radu-Adrian MARINCEAN (2023). RECOMMENDER SYSTEM’S ECONOMIC IMPACT ON E-BUSINESS. A THEORETICAL REVIEW. The Annals of the University of Oradea Economic Sciences DOI
20. Hadi Gholizadeh, Amir M. Fathollahi‐Fard, Hamed Fazlollahtabar, et al. (2022). Fuzzy data-driven scenario-based robust data envelopment analysis for prediction and optimisation of an electrical discharge machine’s parameters. Expert Systems with Applications DOI
21. Genghua Yu, Jia Wu (2022). Efficacy prediction based on attribute and multi-source data collaborative for auxiliary medical system in developing countries. Neural Computing and Applications DOI
22. Pablo Cordero, Manuel Enciso, Domingo López-Rodríguez, et al. (2022). fcaR, Formal Concept Analysis with R. The R Journal DOI
23. Francisco Pérez-Gámez, Domingo López-Rodríguez, Pablo Cordero, et al. (2022). Simplifying Implications with Positive and Negative Attributes: A Logic-Based Approach. Mathematics DOI
24. Francisco Pérez-Gámez, Pablo Cordero, Manuel Enciso, et al. (2022). Computing the Mixed Concept Lattice. Communications in computer and information science DOI
25. Rakhi Seth, Aakanksha Sharaff (2022). A Comparative Overview of Hybrid Recommender Systems: Review, Challenges, and Prospects. DOI
26. Maryam Sajde, Hamed Malek, Mehran Mohsenzadeh (2022). RecoMed: A knowledge-aware recommender system for hypertension medications. Informatics in Medicine Unlocked DOI
27. Genghua Yu, Zhigang Chen, Jia Wu, et al. (2021). Medical decision support system for cancer treatment in precision medicine in developing countries. Expert Systems with Applications DOI
28. Didier Dubois, Jesús Medina, Henri Prade, et al. (2021). Disjunctive attribute dependencies in formal concept analysis under the epistemic view of formal contexts. Information Sciences DOI
29. Ashkan Yeganeh Zaremarjal, Derya Yiltas-Kaplan (2021). Semantic Collaborative Filtering Recommender System Using CNNs. DOI
30. Jingyang Xia, Zhenyang Pi, Weiguo Fang (2021). Predicting War Outcomes Based on a Fuzzy Influence Diagram. International Journal of Fuzzy Systems DOI
31. Rafał Rzepka, Daiki Shirafuji, Akihiko Obayashi (2021). Limits and Challenges of Embedding-based Question Answering in Export Control Expert System. Procedia Computer Science DOI
32. Roberto G. Aragón, M. Eugenia Cornejo, Jesús Medina, et al. (2021). Formal Concept Analysis for Detecting Criminal Patterns. Studies in computational intelligence DOI
33. Rayhan M Auliarahman, Z. K. A. Baizal, Nurul Ikhsan (2021). Conversational Recommender Systems Based on Criticism for Tourist Attractions using TF-IDF. JURNAL MEDIA INFORMATIKA BUDIDARMA DOI
34. Domingo López-Rodríguez, Emilio Muñoz‐Velasco, Manuel Ojeda‐Aciego (2021). Formal Methods in FCA and Big Data. DOI
35. Marco Polignano, Fedelucio Narducci, Andrea Iovine, et al. (2020). HealthAssistantBot: A Personal Health Assistant for the Italian Language. IEEE Access DOI
36. Sandeep K. Sood, Amandeep Kaur, Vaishali Sood (2020). Energy efficient IoT-Fog based architectural paradigm for prevention of Dengue fever infection. Journal of Parallel and Distributed Computing DOI
37. David Griol, Zoraida Callejas, José M. Molina, et al. (2020). Adaptive dialogue management using intent clustering and fuzzy rules. Expert Systems DOI