Papers › Deep Sequence Modeling for Pressure Controlled Mechanical Ventilation

Deep Sequence Modeling for Pressure Controlled Mechanical Ventilation

4 Mar 2022medRxiv 2022 3archive 2025-07-28

Abdelghani Belgaid

This paper presents a deep neural network approach to simulate the pressure of a mechanical ventilator. The traditional mechanical ventilator has a control pressure monitored by a medical practitioner, which could behave inaccurately by missing the proper pressure. This paper exploits recent studies and provides a simulator based on a deep sequence model to predict the airway pressure in the respiratory circuit during the inspiratory phase of a breath given a time series of control parameters and lung attributes. This approach demonstrates the effectiveness of neural network-based controllers in tracking pressure waveforms significantly better than the current industry standard and provides insights to build effective and robust pressure-controlled mechanical ventilators.

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Time SeriesTime Series Analysis

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Time Series Analysis Ventilator Pressure Prediction ResBiLSTM MAE 0.1322 #1 of 1 Archive leaderboard report

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Methods

BiLSTMResBiLSTM

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