RT Journal Article
T1 Integration of the Wang & Mendel algorithm into the application of Fuzzy expert systems to intelligent clinical decision support systems
A1 Casal Guisande, Manuel
A1 Cerqueiro Pequeño, Jorge
A1 Bouza Rodriguez, Jose Benito
A1 Comesaña Campos, Alberto
K1 1203.20 Sistemas de Control Medico
K1 1203.04 Inteligencia Artificial
K1 3212 Salud Publica
AB The use of intelligent systems in clinical diagnostics has evolved, integrating statistical learning and knowledge-based representation models. Two recent works propose the identification of risk factors for the diagnosis of obstructive sleep apnea (OSA). The first uses statistical learning to identify indicators associated with different levels of the apnea-hypopnea index (AHI). The second paper combines statistical and symbolic inference approaches to obtain risk indicators (Statistical Risk and Symbolic Risk) for a given AHI level. Based on this, in this paper we propose a new intelligent system that considers different AHI levels and generates risk pairs for each level. A learning-based model generates Statistical Risks based on objective patient data, while a cascade of fuzzy expert systems determines a Symbolic Risk using symptom data from patient interviews. The aggregation of risk pairs at each level involves a fuzzy expert system with automatically generated fuzzy rules using the Wang-Mendel algorithm. This aggregation produces an Apnea Risk indicator for each AHI level, allowing discrimination between OSA and non-OSA cases, along with appropriate recommendations. This approach improves variability, usefulness, and interpretability, increasing the reliability of the system. Initial tests on data from 4400 patients yielded AUC values of 0.74–0.88, demonstrating the potential benefits of the proposed intelligent system architecture.
PB Mathematics
SN 22277390
YR 2023
FD 2023-05-27
LK http://hdl.handle.net/11093/4901
UL http://hdl.handle.net/11093/4901
LA eng
NO Mathematics, 11(11): 2469 (2023)
NO Xunta de Galicia | Ref. ED481A-2020/038
DS Investigo
RD 16-sep-2024