IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v9y2023i1p2-d1304785.html
   My bibliography  Save this article

Medical Opinions Analysis about the Decrease of Autopsies Using Emerging Pattern Mining

Author

Listed:
  • Isaac Machorro-Cano

    (Tuxtepec Campus, Universidad del Papaloapan, Calle Circuito Central #200, Col. Parque Industrial, San Juan Bautista Tuxtepec C.P. 68301, Oaxaca, Mexico)

  • Ingrid Aylin Ríos-Méndez

    (Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 852, Col. Emiliano Zapata, Orizaba C.P. 94320, Veracruz, Mexico)

  • José Antonio Palet-Guzmán

    (Laboratorios de Anatomía Patológica y Asistencial en Córdoba S.A. de C.V., Av. 9, No. 803, Col. San José, Córdoba C.P. 94560, Veracruz, Mexico)

  • Nidia Rodríguez-Mazahua

    (Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 852, Col. Emiliano Zapata, Orizaba C.P. 94320, Veracruz, Mexico)

  • Lisbeth Rodríguez-Mazahua

    (Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 852, Col. Emiliano Zapata, Orizaba C.P. 94320, Veracruz, Mexico)

  • Giner Alor-Hernández

    (Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 852, Col. Emiliano Zapata, Orizaba C.P. 94320, Veracruz, Mexico)

  • José Oscar Olmedo-Aguirre

    (Escuela Superior de Física y Matemáticas del IPN, Av. Instituto Politécnico Nacional s/n Edificio 9 Unidad Profesional “Adolfo López Mateos”, Col. San Pedro Zacatenco, Ciudad de México C.P. 07738, Mexico)

Abstract

An autopsy is a widely recognized procedure to guarantee ongoing enhancements in medicine. It finds extensive application in legal, scientific, medical, and research domains. However, declining autopsy rates in hospitals constitute a worldwide concern. For example, the Regional Hospital of Rio Blanco in Veracruz, Mexico, has substantially reduced the number of autopsies at hospitals in recent years. Since there are no documented historical records of a decrease in the frequency of autopsy cases, it is crucial to establish a methodological framework to substantiate any actual trends in the data. Emerging pattern mining (EPM) allows for finding differences between classes or data sets because it builds a descriptive data model concerning some given remarkable property. Data set description has become a significant application area in various contexts in recent years. In this research study, various EPM (emerging pattern mining) algorithms were used to extract emergent patterns from a data set collected based on medical experts’ perspectives on reducing hospital autopsies. Notably, the top-performing EPM algorithms were iEPMiner, LCMine, SJEP-C, Top-k minimal SJEPs, and Tree-based JEP-C. Among these, iEPMiner and LCMine demonstrated faster performance and produced superior emergent patterns when considering metrics such as Confidence, Weighted Relative Accuracy Criteria (WRACC), False Positive Rate (FPR), and True Positive Rate (TPR).

Suggested Citation

  • Isaac Machorro-Cano & Ingrid Aylin Ríos-Méndez & José Antonio Palet-Guzmán & Nidia Rodríguez-Mazahua & Lisbeth Rodríguez-Mazahua & Giner Alor-Hernández & José Oscar Olmedo-Aguirre, 2023. "Medical Opinions Analysis about the Decrease of Autopsies Using Emerging Pattern Mining," Data, MDPI, vol. 9(1), pages 1-14, December.
    • Handle: RePEc:gam:jdataj:v:9:y:2023:i:1:p:2-:d:1304785
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/9/1/2/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/9/1/2/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiuming Yu & Meijing Li & Kyung Ah Kim & Jimoon Chung & Keun Ho Ryu, 2016. "Emerging Pattern-Based Clustering of Web Users Utilizing a Simple Page-Linked Graph," Sustainability, MDPI, vol. 8(3), pages 1-18, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alessandro Massaro & Daniele Giannone & Vitangelo Birardi & Angelo Maurizio Galiano, 2021. "An Innovative Approach for the Evaluation of the Web Page Impact Combining User Experience and Neural Network Score," Future Internet, MDPI, vol. 13(6), pages 1-21, May.
    2. Dongwook Kim & Sungbum Kim, 2017. "The Role of Mobile Technology in Tourism: Patents, Articles, News, and Mobile Tour App Reviews," Sustainability, MDPI, vol. 9(11), pages 1-45, November.
    3. Ziyun Deng & Tingqin He, 2018. "A Method for Filtering Pages by Similarity Degree based on Dynamic Programming," Future Internet, MDPI, vol. 10(12), pages 1-12, December.
    4. Xiaoli Wang & Yun Liu & Yanbing Ju, 2018. "Sustainable Public Procurement Policies on Promoting Scientific and Technological Innovation in China: Comparisons with the U.S., the UK, Japan, Germany, France, and South Korea," Sustainability, MDPI, vol. 10(7), pages 1-27, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:9:y:2023:i:1:p:2-:d:1304785. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.