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  1. Article ; Online: Detection of COVID-19 Patients Using Machine Learning Techniques

    Pablo Ormeño / Gastón Márquez / Camilo Guerrero-Nancuante / Carla Taramasco

    International Journal of Environmental Research and Public Health, Vol 19, Iss 8058, p

    A Nationwide Chilean Study

    2022  Volume 8058

    Abstract: Epivigila is a Chilean integrated epidemiological surveillance system with more than 17,000,000 Chilean patient records, making it an essential and unique source of information for the quantitative and qualitative analysis of the COVID-19 pandemic in ... ...

    Abstract Epivigila is a Chilean integrated epidemiological surveillance system with more than 17,000,000 Chilean patient records, making it an essential and unique source of information for the quantitative and qualitative analysis of the COVID-19 pandemic in Chile. Nevertheless, given the extensive volume of data controlled by Epivigila, it is difficult for health professionals to classify vast volumes of data to determine which symptoms and comorbidities are related to infected patients. This paper aims to compare machine learning techniques (such as support-vector machine, decision tree and random forest techniques) to determine whether a patient has COVID-19 or not based on the symptoms and comorbidities reported by Epivigila. From the group of patients with COVID-19, we selected a sample of 10% confirmed patients to execute and evaluate the techniques. We used precision, recall, accuracy, <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>F</mi><mn>1</mn></msub></semantics></math> -score, and AUC to compare the techniques. The results suggest that the support-vector machine performs better than decision tree and random forest regarding the recall, accuracy, <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>F</mi><mn>1</mn></msub></semantics></math> -score, and AUC. Machine learning techniques help process and classify large volumes of data more efficiently and effectively, speeding up healthcare decision making.
    Keywords Epivigila ; machine learning ; symptoms ; comorbidities ; Medicine ; R
    Subject code 006
    Language English
    Publishing date 2022-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Protection Strategy for Edge-Weighted Graphs in Disease Spread

    Ronald Manríquez / Camilo Guerrero-Nancuante / Carla Taramasco

    Applied Sciences, Vol 11, Iss 5115, p

    2021  Volume 5115

    Abstract: Fake news, viruses on computer systems or infectious diseases on communities are some of the problems that are addressed by researchers dedicated to study complex networks. The immunization process is the solution to these challenges and hence the ... ...

    Abstract Fake news, viruses on computer systems or infectious diseases on communities are some of the problems that are addressed by researchers dedicated to study complex networks. The immunization process is the solution to these challenges and hence the importance of obtaining immunization strategies that control these spreads. In this paper, we evaluate the effectiveness of the DIL-W <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mi>α</mi></msup></semantics></math> ranking in the immunization of nodes that are attacked by an infectious disease that spreads on an edge-weighted graph using a graph-based SIR model. The experimentation was done on real and scale-free networks and the results illustrate the benefits of this ranking.
    Keywords edge-weighted graph ; SIR model ; graph protection ; immunization strategy ; complex networks ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 511
    Language English
    Publishing date 2021-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Protection Strategy against an Epidemic Disease on Edge-Weighted Graphs Applied to a COVID-19 Case

    Ronald Manríquez / Camilo Guerrero-Nancuante / Carla Taramasco

    Biology, Vol 10, Iss 667, p

    2021  Volume 667

    Abstract: Among the diverse and important applications that networks currently have is the modeling of infectious diseases. Immunization, or the process of protecting nodes in the network, plays a key role in stopping diseases from spreading. Hence the importance ... ...

    Abstract Among the diverse and important applications that networks currently have is the modeling of infectious diseases. Immunization, or the process of protecting nodes in the network, plays a key role in stopping diseases from spreading. Hence the importance of having tools or strategies that allow the solving of this challenge. In this paper, we evaluate the effectiveness of the DIL-W <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mi>α</mi></msup></semantics></math> ranking in immunizing nodes in an edge-weighted network with 3866 nodes and 6,841,470 edges. The network is obtained from a real database and the spread of COVID-19 was modeled with the classic SIR model. We apply the protection to the network, according to the importance ranking list produced by DIL-W <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mi>α</mi></msup></semantics></math> , considering different protection budgets. Furthermore, we consider three different values for <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math>

    in this way, we compare how the protection performs according to the value of <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math> .
    Keywords edge-weighted graph ; SIR model ; graph protection ; COVID-19 ; Biology (General) ; QH301-705.5
    Subject code 511
    Language English
    Publishing date 2021-07-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: An epidemiological forecast of COVID-19 in Chile based on the generalized SEIR model and the concept of recovered

    Camilo Guerrero-Nancuante / Ronald Manríquez P

    Medwave, Vol 20, Iss 04, Pp e7898-e

    2020  Volume 7898

    Abstract: The COVID-19 pandemic declared by the World Health Organization (WHO) has generated a wide-ranging debate regarding epidemiological forecasts and the global implications. With the data obtained from the Chilean Ministry of Health (MINSAL), a prospective ... ...

    Abstract The COVID-19 pandemic declared by the World Health Organization (WHO) has generated a wide-ranging debate regarding epidemiological forecasts and the global implications. With the data obtained from the Chilean Ministry of Health (MINSAL), a prospective study was carried out using the generalized SEIR model to estimate the course of COVID-19 in Chile. Three scenarios were estimated: Scenario 1 with official MINSAL data; scenario 2 with official MINSAL data and recovery criteria proposed by international organizations of health; and scenario 3 with official MINSAL data, recovery criteria proposed by international organizations of health, and without considering deaths in the total recovered. There are considerable differences between scenario 1 compared to 2 and 3 in the number of deaths, active patients, and duration of the disease. Scenario 3, considered the most adverse, estimates a total of 11,000 infected people, 1,151 deaths, and that the peak of the disease will occur in the first days of May. We concluded that the concept of “recovered” may be decisive for the epidemiological forecasts of COVID-19 in Chile.
    Keywords coronavirus ; epidemiology ; mathematical model ; public health ; Medicine ; R ; Medicine (General) ; R5-920 ; covid19
    Language English
    Publishing date 2020-05-01T00:00:00Z
    Publisher Medwave Estudios Limitada
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Spread of Epidemic Disease on Edge-Weighted Graphs from a Database

    Ronald Manríquez / Camilo Guerrero-Nancuante / Felipe Martínez / Carla Taramasco

    International Journal of Environmental Research and Public Health, Vol 18, Iss 4432, p

    A Case Study of COVID-19

    2021  Volume 4432

    Abstract: The understanding of infectious diseases is a priority in the field of public health. This has generated the inclusion of several disciplines and tools that allow for analyzing the dissemination of infectious diseases. The aim of this manuscript is to ... ...

    Abstract The understanding of infectious diseases is a priority in the field of public health. This has generated the inclusion of several disciplines and tools that allow for analyzing the dissemination of infectious diseases. The aim of this manuscript is to model the spreading of a disease in a population that is registered in a database. From this database, we obtain an edge-weighted graph. The spreading was modeled with the classic SIR model. The model proposed with edge-weighted graph allows for identifying the most important variables in the dissemination of epidemics. Moreover, a deterministic approximation is provided. With database COVID-19 from a city in Chile, we analyzed our model with relationship variables between people. We obtained a graph with 3866 vertices and 6,841,470 edges. We fitted the curve of the real data and we have done some simulations on the obtained graph. Our model is adjusted to the spread of the disease. The model proposed with edge-weighted graph allows for identifying the most important variables in the dissemination of epidemics, in this case with real data of COVID-19. This valuable information allows us to also include/understand the networks of dissemination of epidemics diseases as well as the implementation of preventive measures of public health. These findings are important in COVID-19’s pandemic context.
    Keywords edge-weighted graph ; SIR model ; network ; disease ; COVID-19 ; Medicine ; R
    Subject code 511
    Language English
    Publishing date 2021-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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