Realtime, multimodal invasive ventilation risk monitoring using language models and BoXHED

2024-09-29 · Arash Pakbin, Aaron Su, Donald K. K. Lee, Bobak J. Mortazavi

Objective: realtime monitoring of invasive ventilation (iV) in intensive care units (ICUs) plays a crucial role in ensuring prompt interventions and better patient outcomes. However, conventional methods often overlook valuable insights embedded within clinical notes, relying solely on tabular data. In this study, we propose an innovative approach to enhance iV risk monitoring by incorporating clinical notes into the monitoring pipeline through using language models for text summarization. Results: We achieve superior performance in all metrics reported by the state-of-the-art in iV risk monitoring, namely: an AUROC of 0.86, an AUC-PR of 0.35, and an AUCt of up to 0.86. We also demonstrate that our methodology allows for more lead time in flagging iV for certain time buckets. Conclusion: Our study underscores the potential of integrating clinical notes and language models into realtime iV risk monitoring, paving the way for improved patient care and informed clinical decision-making in ICU settings.

📄 PDF Abstract BibTeX arXiv:2410.03725

Code (0)

등록된 구현이 없습니다.

Tasks

Decision Making Text Summarization

Prospective evaluation of multimodal respiratory failure prediction: Do chest X-rays improve performance beyond EHR signals?

2026-05-25 · Xiaolei Lu, Shamim Nemati arxiv

Early prediction of respiratory failure is critical for timely clinical intervention in intensive care units. Existing electronic health record (EHR)-based models can continuously monitor physiologic deterioration, but t…

Respiratory Failure

Machine Learning for Mechanical Ventilation Control (Extended Abstract)

2021-11-19 · Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai 외

Mechanical ventilation is one of the most widely used therapies in the ICU. However, despite broad application from anaesthesia to COVID-related life support, many injurious challenges remain. We frame these as a control…

BIG-bench Machine Learning Reinforcement Learning (RL)

A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units

2017-04-20 · Niranjani Prasad, Li-Fang Cheng, Corey Chivers, Michael Draugelis 외

The management of invasive mechanical ventilation, and the regulation of sedation and analgesia during ventilation, constitutes a major part of the care of patients admitted to intensive care units. Both prolonged depend…

Management reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Predicting assisted ventilation in Amyotrophic Lateral Sclerosis using a mixture of experts and conformal predictors

2019-07-30 · Telma Pereira, Sofia Pires, Marta Gromicho, Susana Pinto 외

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by a rapid motor decline, leading to respiratory failure and subsequently to death. In this context, researchers have sought for models to …

Conformal Prediction Mixture-of-Experts Respiratory Failure Translation

Classification of Electrical Impedance Tomography Data Using Machine Learning

2021-08-02 · Diogo Pessoa, Bruno Machado Rocha, Grigorios-Aris Cheimariotis, Kostas Haris 외

Patients suffering from pulmonary diseases typically exhibit pathological lung ventilation in terms of homogeneity. Electrical Impedance Tomography (EIT) is a non-invasive imaging method that allows to analyze and quanti…

BIG-bench Machine Learning Classification Diagnostic Feature Engineering