TY - JOUR
T1 - Expert systems in mental health
T2 - innovative approach for personalized treatment
AU - Andrade-Arenas, Laberiano
AU - Rubio-Paucar, Inoc
AU - Celis, Domingo Hernández
AU - Yactayo-Arias, Cesar
N1 - Publisher Copyright:
© 2024 Institute of Advanced Engineering and Science. All rights reserved.
PY - 2024/10
Y1 - 2024/10
N2 - Custom classification of mental illnesses has emerged as a challenge for mental health specialists, often minimized by patients' lack of awareness of symptoms and the importance of early intervention. Therefore, the purpose of this research is to provide a comprehensive understanding of personalized treatment, encompassing both pharmacological and non-pharmacological options, specifically tailored to mental disorders, considering factors such as the patient's age and gender, among other relevant characteristics. In this context, the Buchanan methodology has been chosen as the framework for structuring a web-based expert system. This approach covers everything from problem identification to system implementation and subsequent evaluation. The survey results, with a total of 50 responses, reveal that the category "Good" leads with 70%, closely followed by "Fair" and "Poor," both at 14%. 71.4% of responses reflect a positive evaluation, with 85.7% combining "Good" or "Fair" responses, and all categories reaching 100%. These results support the feasibility and effectiveness of implementing a web-based expert system under the Buchanan methodology. A positive response in the survey suggests that this methodology can significantly contribute to personalizing and recommending appropriate treatments, both pharmacological and non-pharmacological, thereby benefiting a broad spectrum of patients with mental disorders.
AB - Custom classification of mental illnesses has emerged as a challenge for mental health specialists, often minimized by patients' lack of awareness of symptoms and the importance of early intervention. Therefore, the purpose of this research is to provide a comprehensive understanding of personalized treatment, encompassing both pharmacological and non-pharmacological options, specifically tailored to mental disorders, considering factors such as the patient's age and gender, among other relevant characteristics. In this context, the Buchanan methodology has been chosen as the framework for structuring a web-based expert system. This approach covers everything from problem identification to system implementation and subsequent evaluation. The survey results, with a total of 50 responses, reveal that the category "Good" leads with 70%, closely followed by "Fair" and "Poor," both at 14%. 71.4% of responses reflect a positive evaluation, with 85.7% combining "Good" or "Fair" responses, and all categories reaching 100%. These results support the feasibility and effectiveness of implementing a web-based expert system under the Buchanan methodology. A positive response in the survey suggests that this methodology can significantly contribute to personalizing and recommending appropriate treatments, both pharmacological and non-pharmacological, thereby benefiting a broad spectrum of patients with mental disorders.
KW - Buchanan methodology
KW - Comprehensive treatment
KW - Expert system
KW - Mental diseases
KW - Patients
UR - http://www.scopus.com/inward/record.url?scp=85199872890&partnerID=8YFLogxK
U2 - 10.11591/ijeecs.v36.i1.pp414-427
DO - 10.11591/ijeecs.v36.i1.pp414-427
M3 - Original Article
AN - SCOPUS:85199872890
SN - 2502-4752
VL - 36
SP - 414
EP - 427
JO - Indonesian Journal of Electrical Engineering and Computer Science
JF - Indonesian Journal of Electrical Engineering and Computer Science
IS - 1
ER -