RT Journal Article
T1 A conversational recommender system for diagnosis using fuzzy rules.
A1 Cordero-Ortega, Pablo
A1 Enciso-García-Oliveros, Manuel
A1 López-Rodríguez, Domingo
A1 Mora-Bonilla, Ángel
K1 Lógica difusa
K1 Matemáticas -  Uso en diagnóstico
K1 Sistemas expertos
AB 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.
PB Elsevier
YR 2020
FD 2020-09-15
LK https://hdl.handle.net/10630/29666
UL https://hdl.handle.net/10630/29666
LA eng
NO P. Cordero, M. Enciso, D. López, A. Mora, A conversational recommender system for diagnosis using fuzzy rules, Expert Systems with Applications, Volume 154, 2020, 113449, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2020.113449
NO Política de acceso abierto tomada de: https://v2.sherpa.ac.uk/id/publication/4628
NO This work has been partially supported by the projects TIN2017- 89023-P and PGC2018-095869-B-I00 of the Science and Innovation Ministry of Spain, co-funded by the European Regional Develop- ment Fund (ERDF) .
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026