Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System | Paper Citation Record

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This paper cites Global prevalence of COVID-19-induced acute respiratory distress syndrome: systematic review and meta-analysis.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Global prevalence of COVID-19-induced acute respiratory distress syndrome: systematic review and meta-analysis

Reference 1

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Observation b9f1db65-0252-4342-acab-d6ebfc37f20d · outbound

This paper cites The changing epidemiology of mechanical ventilation: a population-based study.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System The changing epidemiology of mechanical ventilation: a population-based study

Reference 2

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This paper cites https://www.who.int/news-room/fact-sheets/detail/ageing- and-health.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System https://www.who.int/news-room/fact-sheets/detail/ageing- and-health

Reference 3

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This paper cites Pathophysiology and classification of respiratory failure.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Pathophysiology and classification of respiratory failure

Reference 4

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This paper cites Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries

Reference 5

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Long-term neurocognitive function after critical illness

Reference 6

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This paper cites Acute Lung Injury and the Acute Respiratory Distress Syn- drome: Pathophysiology and Treatment.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Acute Lung Injury and the Acute Respiratory Distress Syn- drome: Pathophysiology and Treatment

Reference 7

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This paper cites Clinical challenges in mechanical ventilation.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Clinical challenges in mechanical ventilation

Reference 8

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This paper cites Mechanical Ventilation: State of the Art.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Mechanical Ventilation: State of the Art

Reference 9

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Positive Pressure Ventilation

Reference 10

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This paper cites Invasive and non-invasive mechanical ventilation.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Invasive and non-invasive mechanical ventilation

Reference 11

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Observation a444f2c9-2c10-4270-bf49-9a1794c702d3 · outbound

This paper cites The patient needing prolonged mechanical ventilation: a nar- rative review.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System The patient needing prolonged mechanical ventilation: a nar- rative review

Reference 12

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This paper cites Weaning from mechanical ventilation.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Weaning from mechanical ventilation

Reference 13

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Observation 0e63051f-1b6e-41b4-9ac7-275bd307624b · outbound

This paper cites Weaning Patients from the Ventilator.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Weaning Patients from the Ventilator

Reference 14

Resolution: verified exact; doi, observed 2026-08-12T10:56:18.515468Z

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This paper cites Clinical practice, decision-making, and use of clinical decision support systems in invasivemechanicalventilation:anarrativereview.BritishJournalofAnaesthesia 2024 Apr; 0(0).

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Clinical practice, decision-making, and use of clinical decision support systems in invasivemechanicalventilation:anarrativereview.BritishJournalofAnaesthesia 2024 Apr; 0(0)

Reference 15

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Observation a77825ea-d4fd-4865-8e2b-b2004609b558 · outbound

This paper cites The decision to extubate in the intensive care unit.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System The decision to extubate in the intensive care unit

Reference 16

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Observation 7b185186-7727-4ca2-8377-827212f758d0 · outbound

This paper cites Machine learning for predicting successful extubation in patients receiving mechanical ventilation.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Machine learning for predicting successful extubation in patients receiving mechanical ventilation

Reference 17

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Observation cc8eaf70-4380-4b4a-aa22-8473b327c650 · outbound

This paper cites Effect of Failed Extubation on the Outcome of Mechanical Ventilation.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Effect of Failed Extubation on the Outcome of Mechanical Ventilation

Reference 18

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Observation 8991838e-1c11-4c84-b1f9-d124a6c7b6fd · outbound

This paper cites Risk factors for and prediction by caregivers of extubation failure in ICU patients: a prospective study.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Risk factors for and prediction by caregivers of extubation failure in ICU patients: a prospective study

Reference 19

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Observation 33c9ef34-2c68-41a9-bb54-27bf06091bb3 · outbound

This paper cites Variation in extubation failure rates after neonatal congenital heart surgery across Pediatric Cardiac Critical Care Consortium hospitals.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Variation in extubation failure rates after neonatal congenital heart surgery across Pediatric Cardiac Critical Care Consortium hospitals

Reference 20

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This paper cites Extubation Failure in Brain-injured Patients: Risk Factors and Development of a Prediction Score in a Preliminary Prospective Cohort Study.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Extubation Failure in Brain-injured Patients: Risk Factors and Development of a Prediction Score in a Preliminary Prospective Cohort Study

Reference 21

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This paper cites Ventilator Weaning and Spontaneous Breathing Trials; an Educational Review.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Ventilator Weaning and Spontaneous Breathing Trials; an Educational Review

Reference 22

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This paper cites Prolonged Mechanical Ventilation: Outcomes and Man- agement.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Prolonged Mechanical Ventilation: Outcomes and Man- agement

Reference 23

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Observation 7e46bfe5-e4e6-41fe-854e-928bb4fe7a4f · outbound

This paper cites To extubate or not to extubate: Risk factors for extubation failure and deterioration with further mechanical ventilation.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System To extubate or not to extubate: Risk factors for extubation failure and deterioration with further mechanical ventilation

Reference 24

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This paper cites Experience with a step-down respiratory care center at a tertiary referral medical center in Taiwan.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Experience with a step-down respiratory care center at a tertiary referral medical center in Taiwan

Reference 25

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This paper cites The efficacy and effectiveness of machine learning for weaning in mechanically ventilated patients at the intensive care unit: a systematic review.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System The efficacy and effectiveness of machine learning for weaning in mechanically ventilated patients at the intensive care unit: a systematic review

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Resolution: verified exact; doi, observed 2026-08-12T10:56:18.449538Z

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Observation cab3b401-13ec-4e7f-91c3-82bbceb0aab6 · outbound

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Personalized mechanical ventilation in acute respiratory distress syndrome

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Resolution: verified exact; doi, observed 2026-08-12T10:56:18.432510Z

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This paper cites Medical decision support in me- chanical ventilation employing combined model information of gas exchange and respiratory mechanics.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Medical decision support in me- chanical ventilation employing combined model information of gas exchange and respiratory mechanics

Reference 28

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System The role of computer-based clinical decision support systems to deliver protective mechanical ventilation

Reference 29

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Clinical Verification of A Clinical Decision Support System for Ventilator Weaning

Reference 30

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This paper cites An Open-Loop, Physiologic Model–Based DecisionSupportSystemCanProvideAppropriateVentilatorSettings.CriticalCareMedicine 2018 Jul; 46(7):e642–e648.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System An Open-Loop, Physiologic Model–Based DecisionSupportSystemCanProvideAppropriateVentilatorSettings.CriticalCareMedicine 2018 Jul; 46(7):e642–e648

Reference 31

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System CDSS-RM: a clinical decision support system reference model

Reference 32

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This paper cites Barriers to implementation of a computerized decision support system for depression: an observa- tional report on lessons learned in ”real world” clinical settings.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Barriers to implementation of a computerized decision support system for depression: an observa- tional report on lessons learned in ”real world” clinical settings

Reference 33

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Understanding Decision Making in Critical Care

Reference 34

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System A look into the nature and causes of human errors in the intensive care unit

Reference 35

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Documentation, Data, and Decision-Making

Reference 36

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Ventilator Management

Reference 37

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Machine Learning for Mechanical Ventilation Control

Reference 38

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This paper cites Developing an explainable machine learning model to predict the mechanical ventilation duration of patients with ARDS in intensive care units.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Developing an explainable machine learning model to predict the mechanical ventilation duration of patients with ARDS in intensive care units

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This paper cites A novel machine learning model to predict respiratory failure and invasive mechanical ventilation in critically ill patients suffering from COVID-19.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System A novel machine learning model to predict respiratory failure and invasive mechanical ventilation in critically ill patients suffering from COVID-19

Reference 40

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This paper cites Decision to extubate.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Decision to extubate

Reference 41

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Observation ebe074e7-7aa7-4b10-85e6-0ae08bf8e508 · outbound

This paper cites Machine Learning for Prediction of Successful Extubation of Mechanical Ventilated Patients in an Intensive Care Unit: A Retrospective Observational Study.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Machine Learning for Prediction of Successful Extubation of Mechanical Ventilated Patients in an Intensive Care Unit: A Retrospective Observational Study

Reference 42

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This paper cites Mechanical Ventilation to Minimize Progression of Lung Injury in Acute Respiratory Failure.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Mechanical Ventilation to Minimize Progression of Lung Injury in Acute Respiratory Failure

Reference 43

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This paper cites Improvement in the Prediction of Ventilator Weaning Outcomes by an Artificial Neural Network in a Medical ICU.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Improvement in the Prediction of Ventilator Weaning Outcomes by an Artificial Neural Network in a Medical ICU

Reference 44

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Observation 30c464ab-18b1-4828-ab31-57fa532d5faa · outbound

This paper cites An Artificial Neural Network Model for Predicting Successful Extubation in Intensive Care Units.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System An Artificial Neural Network Model for Predicting Successful Extubation in Intensive Care Units

Reference 45

Resolution: verified exact; doi, observed 2026-08-12T10:56:18.285020Z

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This paper cites Rapid shallow breathing index.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Rapid shallow breathing index

Reference 46

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This paper cites The use of the area under the ROC curve in the evaluation of machine learning algorithms.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System The use of the area under the ROC curve in the evaluation of machine learning algorithms

Reference 47

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This paper cites Therapeutic Intervention Scoring System (TISS) - a method for calculating costs in the intensive care unit (ICU) and intermediate care unit (IMCU).

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Therapeutic Intervention Scoring System (TISS) - a method for calculating costs in the intensive care unit (ICU) and intermediate care unit (IMCU)

Reference 48

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Observation 81010108-7f48-419c-a5d6-e4990e7bfc22 · outbound

This paper cites Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units

Reference 49

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This paper cites Prediction of Extubation Failure for Intensive Care Unit Patients Using Light Gradient Boosting Machine.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Prediction of Extubation Failure for Intensive Care Unit Patients Using Light Gradient Boosting Machine

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System CatBoost for big data: an interdisciplinary review

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions

Reference 52

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System LightGBM: A Highly Efficient Gradient Boosting Decision Tree

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System A Machine Learning decision-making tool for extubation in Intensive Care Unit patients

Reference 54

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This paper cites Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Predictors for extubation failure in COVID-19 patients using a machine learning approach

Reference 56

Resolution: verified exact; doi, observed 2026-08-12T10:56:18.202035Z

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This paper cites Scientific Reports 2024 14:1 2024 Feb; 14(1):1–30.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Scientific Reports 2024 14:1 2024 Feb; 14(1):1–30

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Resolution: verified exact; doi, observed 2026-08-12T10:56:18.186709Z

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This paper cites Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability

Reference 58

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System A Unified Approach to Interpreting Model Predictions

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Employing feature engineering strategies to improve the performance of machine learning algorithms on echocardiogram dataset

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges

Reference 61

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Minute ventilation recovery time: a predictor of extubation outcome

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This paper cites Available from:https://www.mdpi.com/2076-3417/13/ 12/7082.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Available from:https://www.mdpi.com/2076-3417/13/ 12/7082

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Designing an Interpretability-Based Model to Explain the Arti- ficial Intelligence Algorithms in Healthcare

Reference 64

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This paper cites Chest 2003 Jul; 124(1):262–8.doi: 10.1378/CHEST.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Chest 2003 Jul; 124(1):262–8.doi: 10.1378/CHEST

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Deep Learning for Time Series Fore- casting: Advances and Open Problems

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Analyzing Patient Trajectories with Artificial Intelligence

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Technology investigation on time series classification and prediction

Reference 68

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls

Reference 69

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Long Short-Term Memory

Reference 70

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Recurrent neural networks and time series prediction

Reference 71

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Long Short-Term Memory Recurrent Neural Network for Automatic Speech Recognition

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Natural language processing: state of the art, current trends and challenges

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Resolution: verified exact; doi, observed 2026-08-12T10:56:18.087832Z

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm

Reference 74

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 75

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Convolutional neural networks: an overview and application in radiology

Reference 76

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Temporal Convolutional Networks: A Unified Approach to Action Segmentation

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Partial dependence through stratification

Reference 78

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Temporal convolutional networks allow early prediction of events in critical care

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Resolution: verified exact; doi, observed 2026-08-12T10:56:18.054545Z

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This paper cites Interpretable recurrent neural network models for dynamic prediction of the extubation failure risk in patients with invasive mechanical ventilation in the intensive care unit.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Interpretable recurrent neural network models for dynamic prediction of the extubation failure risk in patients with invasive mechanical ventilation in the intensive care unit

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Developing and validating a machine learning model to predict successful next-day extubation in the ICU

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Resolution: verified exact; doi, observed 2026-08-12T10:56:18.038078Z

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Fallacies of last observation carried forward analyses

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Effect of sequence padding on the perfor- mance of deep learning models in archaeal protein functional prediction

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Resolution: verified exact; doi, observed 2026-08-12T10:56:18.020931Z

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Moving from bytes to bedside: a systematic review on the use of artificial intelligence in the intensive care unit

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System The perceptron: A probabilistic model for information storage and organiza- tion in the brain

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System doi: 10.1007/BF02478259/ METRICS

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Activation Functions in Artificial Neural Networks: A Systematic Overview

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Appli- cations and Research Directions

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Conceptual Understanding of Convolu- tional Neural Network- A Deep Learning Approach

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System A review on the long short-term memory model

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Ensemble Dilated Convolutional Neural Network and Its Application in Rotating Machinery Fault Diagnosis

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Resolution: verified exact; doi, observed 2026-08-12T10:56:17.948372Z

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Observation 89ecc235-137d-4996-9e1a-3a6a86374a37 · outbound

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System An adversarial discriminative temporal convolutional network for EEG-based cross-domain emotion recognition

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System MIMIC-IV (version 3.0)

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Temporal con- volutional networks and data rebalancing for clinical length of stay and mortality prediction

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Resolution: verified exact; doi, observed 2026-08-12T10:56:17.931179Z

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Observation 43fb59e0-7e34-4286-81e4-3beecdb5068d · outbound

This paper cites PhysioBank, PhysioToolkit, and PhysioNet: compo- nents of a new research resource for complex physiologic signals.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System PhysioBank, PhysioToolkit, and PhysioNet: compo- nents of a new research resource for complex physiologic signals

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Lehman L wei, Celi LA, and Mark RG

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Observation 24cdc924-5d24-4b08-b9ec-35ef4b36b8e3 · outbound

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Decision support system to evaluate ventilation in the acute respiratory distress syndrome (DeVENT study)—trial protocol

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Observation 11966c92-d365-4960-9785-3d9699e33474 · outbound

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Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System Unresolved cited work

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This paper cites A new method of classifying prognostic comorbidityinlongitudinalstudies:Developmentandvalidation.JournalofChronicDiseases 1987 Jan; 40(5):373–83.

Predicting Extubation Failure in Intensive Care: The Development of a Novel, End-to-End Actionable and Interpretable Prediction System A new method of classifying prognostic comorbidityinlongitudinalstudies:Developmentandvalidation.JournalofChronicDiseases 1987 Jan; 40(5):373–83

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