dor_id: 4110123
506.#.#.a: Público
590.#.#.d: Los artículos enviados a la revista "Journal of Applied Research and Technology", se juzgan por medio de un proceso de revisión por pares
510.0.#.a: Scopus, Directory of Open Access Journals (DOAJ); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Indice de Revistas Latinoamericanas en Ciencias (Periódica); La Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc); Consejo Nacional de Ciencia y Tecnología (CONACyT); Google Scholar Citation
561.#.#.u: https://www.icat.unam.mx/
650.#.4.x: Ingenierías
336.#.#.b: article
336.#.#.3: Artículo de Investigación
336.#.#.a: Artículo
351.#.#.6: https://jart.icat.unam.mx/index.php/jart
351.#.#.b: Journal of Applied Research and Technology
351.#.#.a: Artículos
harvesting_group: RevistasUNAM
270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx
590.#.#.c: Open Journal Systems (OJS)
270.#.#.d: MX
270.1.#.d: México
590.#.#.b: Concentrador
883.#.#.u: https://revistas.unam.mx/catalogo/
883.#.#.a: Revistas UNAM
590.#.#.a: Coordinación de Difusión Cultural
883.#.#.1: https://www.publicaciones.unam.mx/
883.#.#.q: Dirección General de Publicaciones y Fomento Editorial
850.#.#.a: Universidad Nacional Autónoma de México
856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/670/646
100.1.#.a: Gopalakrishnan, Vinodhini; Ramaswamy, Chandrasekaran
524.#.#.a: Gopalakrishnan, Vinodhini, et al. (2017). Patient opinion mining to analyze drugs satisfaction using supervised learning. Journal of Applied Research and Technology; Vol. 15 Núm. 4. Recuperado de https://repositorio.unam.mx/contenidos/4110123
245.1.0.a: Patient opinion mining to analyze drugs satisfaction using supervised learning
502.#.#.c: Universidad Nacional Autónoma de México
561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM
264.#.0.c: 2017
264.#.1.c: 2019-06-11
653.#.#.a: Sentiment; Opinion; Helath; Drugs; Classification
506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx
884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/670
001.#.#.#: 074.oai:ojs2.localhost:article/670
041.#.7.h: eng
520.3.#.a: Opinion mining is a very challenging problem, since user generated content is described in various complex ways using natural language. In opinion mining, most of the researchers have worked on general domains such as electronic products, movies, and restaurants reviews but not much on health and medical domains. Patients using drugs are often looking for stories from patients like them on the internet which they cannot always find among their friends and family. Few studies investigating the impact of social media on patients have shown that for some health problems, online community support results in a positive effect. The opinion mining method employed in this work focuses on predicting the drug satisfaction level among the other patients who already experienced the effect of a drug. This work aims to apply neural network based methods for opinion mining from social web in health care domain. We have extracted the reviews of two different drugs. Experimental analysis is done to analyze the performance of classification methods on reviews of two different drugs. The results demonstrate that neural network based opinion mining approach outperforms the support vector machine method in terms of precision, recall and f-score. It is also shown that the performance of radial basis function neural network method is superior than probabilistic neural network method in terms of the performance measures used.
773.1.#.t: Journal of Applied Research and Technology; Vol. 15 Núm. 4
773.1.#.o: https://jart.icat.unam.mx/index.php/jart
022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423
310.#.#.a: Bimestral
264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM
doi: https://doi.org/10.1016/j.jart.2017.02.005
harvesting_date: 2023-11-08 13:10:00.0
856.#.0.q: application/pdf
file_creation_date: 2017-08-29 10:35:57.0
file_modification_date: 2017-08-29 05:07:36.0
file_creator: Vinodhini Gopalakrishnan
file_name: 79f76f10936b7534591ab92f4e489f7c3f39284c3c463b7aaa9b2f2f0321ea82.pdf
file_pages_number: 9
file_format_version: application/pdf; version=1.7
file_size: 1001058
last_modified: 2024-03-19 14:00:00
license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es
license_type: by-nc-sa
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