BACKGROUND: Chronic respiratory diseases often require long-term ventilatory support, leading to a growing number of patients treated with home mechanical ventilation (HMV). Despite advancements in telemonitoring with real-time tracking of noninvasiv...
OBJECTIVE: This retrospective cohort study aimed to systematically evaluate the impact of different mechanical ventilation strategies on postoperative pulmonary complications (PPCs) in thoracic surgery and to establish a risk prediction model that fa...
UNLABELLED: Prognostic scores such as the Pediatric Index of Mortality (PIM-3) are widely used to estimate mortality risk in PICUs, yet their performance in low- and middle-income countries (LMICs) remains uncertain. We aimed to evaluate the predicti...
BMC medical informatics and decision making
Oct 13, 2025
BACKGROUND: Clinical utilization of machine learning is hampered by the lack of interpretability inherent in most non-linear black box modeling approaches, reducing trust among clinicians and regulators. Advanced large language models offer a potenti...
BACKGROUND: Adequate ventilation in mechanically ventilated patients is contingent upon the monitoring of the arterial partial pressure of carbon dioxide (PaCO2) during general anesthesia. Despite its significance, continuous monitoring remains chall...
High-tech mechanical ventilators are engineered to deliver precise and consistent airflow, which is critical for effective respiratory therapy. This study evaluates flow control performance in a custom-built electro-pneumatic ventilator prototype, co...
Criteria to identify patients who are ready to be liberated from mechanical ventilation (MV) are imprecise, often resulting in prolonged MV or reintubation, both of which are associated with adverse outcomes. Daily protocol-driven assessment of the n...
INTRODUCTION: Patient-ventilator asynchrony (PVA) is a common and harmful complication during mechanical ventilation, often requiring labor-intensive manual assessment. Machine learning (ML) offers a promising approach for automated and accurate PVA ...
. Air trapping is a major symptom of respiratory diseases like chronic obstructive pulmonary disease and asthma, and has always been a significant problem in treating patients using mechanical ventilation. If not handled timely, it can pose risk of s...
OBJECTIVES: The objective of this study is to evaluate whether large language models (LLMs) can achieve performance comparable to expert-developed deep neural networks in detecting flow starvation (FS) asynchronies during mechanical ventilation.
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