onyxRay

Pinoliad, Sholomon L.; Dichoso, Duanne Austin N.; Caballero, Arlene R.; Albina, Erlito M.

doi:10.1145/3411681.3411698

Cited by 6 publications

(5 citation statements)

References 19 publications

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“…The execution of the SLR protocol yielded 26 primary studies, which were considered eligible. Our findings reveal a substantial diversification of algorithmic models, regardless of the purpose of application, and three subareas of concentration in the field of health sciences: (1) surveillance (16 studies—61.54%) ( 31 – 46 ); (2) diagnosis (nine studies—34.62%) ( 47 – 55 ); and (3) evaluation of health policies (one study—3.85%) ( 56 ).…”

Section: Discussionmentioning

confidence: 88%

“…Other computational approaches include models based on Deep Learning ( 43 , 49 , 55 ), Convolutional Neural Network Ensemble ( 51 ), Decision Tree ( 47 ), RF ( 31 , 49 , 50 ), Gradient Boosting Machine ( 49 ), Extreme Gradient Boosting (XGBoost) ( 47 – 49 ), Autoregressive Integrated Moving Average (ARIMA) ( 33 , 38 , 41 ), ARIMA with Explanatory Variable ( 38 ), Decomposition ( 38 ), Generalized Estimating Equations ( 36 ), NLP ( 37 , 45 ), Ontology ( 42 ), Complex Networks ( 46 ), Knowledge Embedding Representation ( 40 ), Sexual Infections as Large-Scale Agent-based Simulation model ( 44 ), and Gray Model ( 39 ). Table 4 shows the techniques that obtained the best performances in each study and their respective values according to the metric used for evaluation.…”

Section: Resultsmentioning

confidence: 99%

“…The primary included studies show and explore various applications of computational methods in the context of the syphilis. Two large groups of applications stood out: first, in the classification and identification syphilis indicators ( 47 – 55 ); second, in the prediction of STI-related risks, including syphilis ( 31 – 36 ). Both groups employed trained computational models that have learned patterns from a previously known syphilis-related dataset.…”

Section: Resultsmentioning

confidence: 99%

“…Considering the perspective of the large area of health sciences, the applications proposed in the included studies focus on seeking and investigating computational solutions within the scope of three subareas ( Figure 2 ). (1) surveillance accounted for 16 studies (61.54%) ( 31 – 46 ); (2) diagnosis for nine related studies (34.62%) ( 47 – 55 ); and (3) evaluation of health policies for only one (3.85%) ( 56 ).…”

Section: Resultsmentioning

confidence: 99%

“…For (1) surveillance, studies ( 31 – 46 ) point to promising technologies or computational methods (Sections 3.1 and 3.2) that act as instruments to subsidize and provide technical support to actions mainly related to the epidemiological surveillance of syphilis and other STIs. Not diverging from the purpose of the different subareas, subarea (2) stood out, where studies focus on seeking innovative and scalable solutions for diagnosing syphilis and other STIs ( 47 – 55 ). Regarding (3) evaluation of health policies, Pinto et al ( 56 ) present a computational solution to investigate and statistically measure the effectiveness of strategies and public policy actions which, from the perspective of public health management, is a vital resource to assist and guide decision-making.…”

Section: Resultsmentioning

confidence: 99%

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Computational methods applied to syphilis: where are we, and where are we going?

Albuquerque,

Fernandes,

Barbalho

et al. 2023

Front. Public Health

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Syphilis is an infectious disease that can be diagnosed and treated cheaply. Despite being a curable condition, the syphilis rate is increasing worldwide. In this sense, computational methods can analyze data and assist managers in formulating new public policies for preventing and controlling sexually transmitted infections (STIs). Computational techniques can integrate knowledge from experiences and, through an inference mechanism, apply conditions to a database that seeks to explain data behavior. This systematic review analyzed studies that use computational methods to establish or improve syphilis-related aspects. Our review shows the usefulness of computational tools to promote the overall understanding of syphilis, a global problem, to guide public policy and practice, to target better public health interventions such as surveillance and prevention, health service delivery, and the optimal use of diagnostic tools. The review was conducted according to PRISMA 2020 Statement and used several quality criteria to include studies. The publications chosen to compose this review were gathered from Science Direct, Web of Science, Springer, Scopus, ACM Digital Library, and PubMed databases. Then, studies published between 2015 and 2022 were selected. The review identified 1,991 studies. After applying inclusion, exclusion, and study quality assessment criteria, 26 primary studies were included in the final analysis. The results show different computational approaches, including countless Machine Learning algorithmic models, and three sub-areas of application in the context of syphilis: surveillance (61.54%), diagnosis (34.62%), and health policy evaluation (3.85%). These computational approaches are promising and capable of being tools to support syphilis control and surveillance actions.

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