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Analysis of institutional authors

Giraldo, Beatriz FAuthor
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Development of a Deep Learning Model for the Prediction of Ventilator Weaning

Publicated to:International Journal Of Online And Biomedical Engineering. 20 (11): 161-178 - 2024-08-08 20(11), DOI: 10.3991/ijoe.v20i11.49453

Authors: González, H; Arizmendi, CJ; Giraldo, BF

Affiliations

Barcelona Inst Sci & Technol, Inst Bioengn Catalonia IBEC, Barcelona, Spain - Author
Biomedical Signal Processing and Interpretation. Institute for Bioengineering of Catalonia - Author
CIBER Bioingn Biomat & Nanomed, Madrid, Spain - Author
Univ Autonoma Bucaramanga, Bucaramanga, Colombia - Author
Univ Politecn Catalunya Barcelona Tech UPC, Barcelona, Spain - Author
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Abstract

The issue of failed weaning is a critical concern in the intensive care unit (ICU) setting. This scenario occurs when a patient experiences difficulty maintaining spontaneous breathing and ensuring a patent airway within the first 48 hours after the withdrawal of mechanical ventilation. Approximately 20% of ICU patients experience this phenomenon, which has severe repercussions on their health. It also has a substantial impact on clinical evolution and mortality, which can increase by 25% to 50%. To address this issue, we propose a medical support system that uses a convolutional neural network (CNN) to assess a patient's suitability for disconnection from a mechanical ventilator after a spontaneous breathing test (SBT). During SBT, respiratory flow and electrocardiographic activity were recorded and after processed using time-frequency analysis (TFA) techniques. Two CNN architectures were evaluated in this study: one based on ResNet50, with parameters tuned using a Bayesian optimization algorithm, and another CNN designed from scratch, with its structure also adapted using a Bayesian optimization algorithm. The WEANDB database was used to train and evaluate both models. The results showed remarkable performance, with an average accuracy 98 +/- 1.8% when using CNN from scratch. This model has significant implications for the ICU because it provides a reliable tool to enhance patient care by assisting clinicians in making timely and accurate decisions regarding weaning. This can potentially reduce the adverse outcomes associated with failed weaning events.

Keywords
Bayesian optimization algorithm (boaContinuous wavelet transform (cwt)ConvolutionalExtubationFailurIntensive-care-unitNeural network (cnn) from scratchRespiratory-distress-syndromeTime-frequency analysis (tfa)Weaning

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal International Journal Of Online And Biomedical Engineering due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), 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 , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Engineering (Miscellaneous). Notably, the journal is positioned en el Cuartil Q3 for the agency WoS (JCR) in the category Computer Science, Interdisciplinary Applications.

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 2025-05-23:

  • WoS: 2
  • 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 2025-05-23:

  • 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: 4 (PlumX).

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

This work has been carried out with international collaboration, specifically with researchers from: Colombia.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (Giraldo Giraldo, Beatriz).