Research graph
References from Harnessing artificial intelligence to modulate mechanical power: Toward safer and outcome-oriented ventilation in critical care. Local targets link to admitted publications; unresolved targets remain external evidence.
Ventilator-related causes of lung injury: the mechanical power
10.1007/s00134-016-4505-2 · 2016 · External reference
Mechanical power and ventilator-induced lung injury: what does physics have to say?
10.1164/rccm.202307-1292vp · 2024 · External reference
Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts
10.1007/s00134-018-5375-6 · 2018 · External reference
High mechanical power and driving pressures are associated with postoperative respiratory failure independent from patients’ respiratory system mechanics
10.1097/ccm.0000000000006038 · 2024 · External reference
A validation study of a continuous automatic measurement of the mechanical power in ARDS patients
10.1016/j.jcrc.2021.09.009 · 2022 · External reference
SOLVe: a closed-loop system focused on protective mechanical ventilation
10.1186/s12938-023-01111-0 · 2023 · External reference
Adaptive mechanical ventilation with automated minimization of mechanical power-a pilot randomized cross-over study
10.1186/s13054-019-2610-7 · 2019 · External reference
Use of machine learning to screen for acute respiratory distress syndrome using raw ventilator waveform data
2021 · External reference
Optimizing mechanical ventilation: personalizing mechanical power to reduce ICU mortality - a retrospective cohort study
10.1371/journal.pone.0318018 · 2025 · External reference
Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias
10.1016/j.bja.2021.09.025 · 2022 · External reference
Insights into the problem of alarm fatigue with physiologic monitor devices: a comprehensive observational study of consecutive intensive care unit patients
10.1371/journal.pone.0110274 · 2014 · External reference
Automation bias: a systematic review of frequency, effect mediators, and mitigators
10.1136/amiajnl-2011-000089 · 2012 · External reference
Five things every clinician should know about AI ethics in intensive care
10.1007/s00134-020-06277-y · 2021 · External reference
Legal and ethical consideration in artificial intelligence in healthcare: who takes responsibility?
10.3389/fsurg.2022.862322 · 2022 · External reference
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
10.1038/s41591-022-01772-9 · 2022 · External reference
