A clinical decision-support system for dengue based on fuzzy cognitive maps
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Health Professions,Medicine (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s10729-022-09611-6.pdf
Reference46 articles.
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2. Caicedo-Borrero DM, Tovar JR, Mendez A, Parra B, Bonelo A, Celis J, Villegas L, Collazos C, Osorio L (2020) Development and performance of dengue diagnostic clinical algorithms in Colombia. Am J Trop Med Hyg 102:1226–1236. https://doi.org/10.4269/ajtmh.19-0722
3. World Health Organization (2020) Dengue and severe dengue. https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue. Accessed 29 Jul 2022
4. Jaenisch T, Tam DTH, Kieu NTT, Ngoc T, Nam NT, Van Kinh N, Yacoub S, Chanpheaktra N, Kumar V, See LLC, Sathar J, Sandoval EP, Alfaro GMM, Laksono IS, Mahendradhata Y, Sarker M, Ahmed F, Caprara A, Benevides BS, Marques ET, Magalhaes T, Brasil P, Netto M, Tami A, Bethencourt SE, Guzman M, Simmons C, Quyen NTH, Merson L, Dung NTP, Beck D, Wirths M, Wolbers M, Lam PK, Rosenberger K, Wills B (2016) Clinical evaluation of dengue and identification of risk factors for severe disease: Protocol for a multicentre study in 8 countries. BMC Infect Dis 16:120. https://doi.org/10.1186/s12879-016-1440-3
5. Wong PF, Wong LP, AbuBakar S (2020) Diagnosis of severe dengue: Challenges, needs and opportunities. J Infect Public Health 13:193–198. https://doi.org/10.1016/j.jiph.2019.07.012
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