This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1478) Artificial Intelligence (2006) Machine Learning (1984) Clinical Information and Decision Making (1821) Perioperative Risk Assessment (26) Artificial Intelligence in Surgery and Perioperative Medicine (41)

Published on in Vol 9, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31311, first published .
Short-Term Event Prediction in the Operating Room (STEP-OP) of Five-Minute Intraoperative Hypotension Using Hybrid Deep Learning: Retrospective Observational Study and Model Development

Short-Term Event Prediction in the Operating Room (STEP-OP) of Five-Minute Intraoperative Hypotension Using Hybrid Deep Learning: Retrospective Observational Study and Model Development

Short-Term Event Prediction in the Operating Room (STEP-OP) of Five-Minute Intraoperative Hypotension Using Hybrid Deep Learning: Retrospective Observational Study and Model Development

Authors of this article:

Sooho Choe1 Author Orcid Image ;   Eunjeong Park2 Author Orcid Image ;   Wooseok Shin3 Author Orcid Image ;   Bonah Koo4 Author Orcid Image ;   Dongjin Shin5 Author Orcid Image ;   Chulwoo Jung6 Author Orcid Image ;   Hyungchul Lee6 Author Orcid Image ;   Jeongmin Kim7 Author Orcid Image
Article Authors Cited by (12) Tweetations (4) Metrics

Journals

  1. Pinsky M, Cecconi M, Chew M, De Backer D, Douglas I, Edwards M, Hamzaoui O, Hernandez G, Martin G, Monnet X, Saugel B, Scheeren T, Teboul J, Vincent J. Effective hemodynamic monitoring. Critical Care 2022;26(1) View
  2. Davoud S, Kovacheva V. On the Horizon: Specific Applications of Automation and Artificial Intelligence in Anesthesiology. Current Anesthesiology Reports 2023;13(2):31 View
  3. Ripollés-Melchor J, Ruiz-Escobar A, Fernández-Valdes-Bango P, Lorente J, Jiménez-López I, Abad-Gurumeta A, Carrasco-Sánchez L, Monge-García M. Hypotension prediction index: From reactive to predictive hemodynamic management, the key to maintaining hemodynamic stability. Frontiers in Anesthesiology 2023;2 View
  4. Shi M, Zheng Y, Wu Y, Ren Q. Multitask Attention-Based Neural Network for Intraoperative Hypotension Prediction. Bioengineering 2023;10(9):1026 View
  5. Mohammadi I, Firouzabadi S, Hosseinpour M, Akhlaghpasand M, Hajikarimloo B, Tavanaei R, Izadi A, Zeraatian-Nejad S, Eghbali F. Predictive ability of hypotension prediction index and machine learning methods in intraoperative hypotension: a systematic review and meta-analysis. Journal of Translational Medicine 2024;22(1) View
  6. Hwang E, Park Y, Kim J, Park S, Kim J, Kim S. Intraoperative Hypotension Prediction Based on Features Automatically Generated Within an Interpretable Deep Learning Model. IEEE Transactions on Neural Networks and Learning Systems 2024;35(10):13887 View
  7. Mukkamala R, Schnetz M, Khanna A, Mahajan A. Intraoperative Hypotension Prediction: Current Methods, Controversies, and Research Outlook. Anesthesia & Analgesia 2025;141(1):61 View
  8. Yang H, Celi L, Lee H, Park S, Lee S, Jung C, Lee H. The effect of selection bias on the performance of a deep learning-based intraoperative hypotension prediction model using real-world samples from a publicly available database. British Journal of Anaesthesia 2025;135(3):571 View
  9. Zhu Z, Zhao Q, Ge Y, Li J, Wang S, Yang J. LEGN: A large language model-guided event graph network for intraoperative hypotension prediction. Expert Systems with Applications 2025;294:128677 View
  10. Chaari N, Winski G, Hallbäck M, Lundström N, Björne H, Jacobsson M. Towards reliable prediction of intraoperative hypotension: a cross-center evaluation of deep learning-based and MAP-derived methods. Journal of Clinical Monitoring and Computing 2025 View

Conference Proceedings

  1. Jeong H, Kim J, Jeong J, Kim H. 2022 IEEE International Conference on Big Data (Big Data). Deep Learning Models with Stratification-based Loss Function on Domain Knowledge-based Time series Data: Hypotension Prediction View
  2. Yang K, Ren M, Xu J, Zeng X. 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Dynamic Prediction of Intraoperative Hypotension Based on Hemodynamic Monitoring Data With a Transformer-Based Deep Learning Model View