ML Anthology

A Risk Prediction Framework to Optimize Remote Patient Monitoring Following Cardiothoracic Surgery

Ricardo Santos, Bruno Ribeiro, Pedro Dias, Isabel Curioso, Pedro Madeira, Federico Guede-Fernández, Jorge Santos, Pedro Coelho, Inês Sousa, Ana Londral
ECML-PKDD 2023 pp. 366-371
doi:10.1007/978-3-031-43430-3_32 /ecmlpkdd/2023/santos2023ecmlpkdd-risk/

Abstract

Remote Patient Monitoring (RPM) in cardiac surgery can become valuable for clinicians to follow patients post-discharge closely. However, these services require additional and frequently limited human and technical resources. We present the CardioFollow. AI Framework, a decision support system to assist doctors in selecting patients to be monitored remotely. Currently supporting a clinical trial, it leverages a Machine Learning model to predict the risk of post-discharge complications. Interpretable assessments are included so that clinicians can evaluate individual predictions. Additionally, the user-friendly interface of the CardioFollow. AI Framework enhances the follow-up of discharged patients by granting access to centralised information. This paper outlines the design and implementation of the CardioFollow. AI Framework and its potential impact on improving personalised patient careq.

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Text

Santos et al. "A Risk Prediction Framework to Optimize Remote Patient Monitoring Following Cardiothoracic Surgery." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023. doi:10.1007/978-3-031-43430-3_32

Markdown

[Santos et al. "A Risk Prediction Framework to Optimize Remote Patient Monitoring Following Cardiothoracic Surgery." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023.](https://mlanthology.org/ecmlpkdd/2023/santos2023ecmlpkdd-risk/) doi:10.1007/978-3-031-43430-3_32

BibTeX

@inproceedings{santos2023ecmlpkdd-risk,
  title     = {{A Risk Prediction Framework to Optimize Remote Patient Monitoring Following Cardiothoracic Surgery}},
  author    = {Santos, Ricardo and Ribeiro, Bruno and Dias, Pedro and Curioso, Isabel and Madeira, Pedro and Guede-Fernández, Federico and Santos, Jorge and Coelho, Pedro and Sousa, Inês and Londral, Ana},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2023},
  pages     = {366-371},
  doi       = {10.1007/978-3-031-43430-3_32},
  url       = {https://mlanthology.org/ecmlpkdd/2023/santos2023ecmlpkdd-risk/}
}