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Grant support

This work was supported by Instituto de Salud Carlos III, Spain (ISCIII) [project PI21/00064] and co-funded by the European Union; Universitat Rovira i Virgili (URV) [projects number 2023PFR-URV-114, 2022PFR-URV-41]; ITAKA funding from AGAUR [2021-SGR-00114]; and the first author had a pre-doctoral FI grant from Generalitat de Catalunya and Fons Social Europeu [grant number 2022 FI_B1 00036].

Analysis of institutional authors

Pascual-Fontanilles, JordiCorresponding AuthorValls, AidaAuthorRomero-Aroca, PedroAuthor
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Article

Multivariate data binning and examples generation to build a Diabetic Retinopathy classifier based on temporal clinical and analytical risk factors

Publicated to:Knowledge-Based Systems. 300 112154- - 2024-09-27 300(), DOI: 10.1016/j.knosys.2024.112154

Authors: Pascual-Fontanilles, Jordi; Valls, Aida; Romero-Aroca, Pedro

Affiliations

Hosp Univ St Joan de Reus, Serv Oftalmol, Catalonia, Spain - Author
Inst Invest Sanitaria Pere Virgili, Catalonia, Spain - Author
TecnATox, Ctr Environm Food & Toxicol Technol, Reus, Spain - Author
Univ Rovira & Virgili, Dept Engn Informat & Matemat, ITAKA, Av Paisos Catalans 26, Tarragona 43007, Catalonia, Spain - Author

Abstract

In this paper, we explore the possibility of exploiting retrospective clinical data from Electronic Health Records (EHR) for classification tasks in chronic patients. The different intervals, short length and high class imbalance make it unfeasible to use traditional time series techniques. The first contribution of the paper is a preprocessing method to construct a multivariate time series dataset using EHR data, which infers missing data and regularizes the data frequency. The second contribution addresses class imbalance by using domain knowledge and existing short EHR series. We synthetically extrapolate patients' data by using similar long time series and a fuzzy-based approach. The paper addresses the problem of detection of Diabetic Retinopathy (DR). Expert domain knowledge from ophthalmologists has been used in the proposed techniques to guide the processing of time series. The novelty in that case study consists in not using eye-fundus image analysis. Instead, the proposed methods are based solely on EHR data. Several multivariate multiclass time series classifiers are used to detect the four levels of DR severity from the pre -processed data sequences. Experiments prove the quality of the sequence preprocessing techniques proposed for EHR data. Results indicate that the TapNet classifier is the best one for DR grading. Despite being tested for DR detection, the proposed data preparation methods are applicable to other diseases with similar characteristics.

Keywords
Class imbalanceClassificationClinical decision support systemsDiabetic retinopathDiabetic retinopathyFuzzy logicTime series classification

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Knowledge-Based Systems due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 27/197, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Artificial Intelligence.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-05-10:

  • WoS: 1
  • Scopus: 2
Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-10:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 23 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

    It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

    • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
    Leadership analysis of institutional authors

    There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Pascual Fontanilles, Jordi) and Last Author (Romero Aroca, Pedro).

    the author responsible for correspondence tasks has been Pascual Fontanilles, Jordi.