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Respiratory Distress Syndrome

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[Severe influenza A (H1N1) in late pregnancy: a case report].

Zhonghua wei zhong bing ji jiu yi xue
Pregnancy has increased susceptibility to H1N1 influenza virus infection. Maternal influenza infection is associated with increased risk of morbidity and mortality. A case of influenza A (H1N1) during late pregnancy (pregnancy 1, birth 0, pregnancy 3...

Towards Reliable ARDS Clinical Decision Support: ARDS Patient Analytics with Free-text and Structured EMR Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In this work, we utilize a combination of free-text and structured data to build Acute Respiratory Distress Syndrome(ARDS) prediction models and ARDS phenotype clusters. We derived 'Patient Context Vectors' representing patientspecific contextual ARD...

[Research on algorithms for identifying the severity of acute respiratory distress syndrome patients based on noninvasive parameters].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Acute respiratory distress syndrome (ARDS) is a serious threat to human life and health disease, with acute onset and high mortality. The current diagnosis of the disease depends on blood gas analysis results, while calculating the oxygenation index....

Predictive model for acute respiratory distress syndrome events in ICU patients in China using machine learning algorithms: a secondary analysis of a cohort study.

Journal of translational medicine
BACKGROUND: To develop a machine learning model for predicting acute respiratory distress syndrome (ARDS) events through commonly available parameters, including baseline characteristics and clinical and laboratory parameters.

Multi-resolution convolutional neural networks for fully automated segmentation of acutely injured lungs in multiple species.

Medical image analysis
Segmentation of lungs with acute respiratory distress syndrome (ARDS) is a challenging task due to diffuse opacification in dependent regions which results in little to no contrast at the lung boundary. For segmentation of severely injured lungs, loc...

Deep CNN Sparse Coding for Real Time Inhaler Sounds Classification.

Sensors (Basel, Switzerland)
Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indicates, medication adherence can effectively be monitored by successfully identifying actions performe...

Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS).

Journal of critical care
PURPOSE: Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with high mortality and associated morbidity. The objective of this study is to develop and evaluate a novel application of gradient boosted tree models trained on...

Analytics with artificial intelligence to advance the treatment of acute respiratory distress syndrome.

Journal of evidence-based medicine
Artificial intelligence (AI) has found its way into clinical studies in the era of big data. Acute respiratory distress syndrome (ARDS) or acute lung injury (ALI) is a clinical syndrome that encompasses a heterogeneous population. Management of such ...

Transfer learning with chest X-rays for ER patient classification.

Scientific reports
One of the challenges with urgent evaluation of patients with acute respiratory distress syndrome (ARDS) in the emergency room (ER) is distinguishing between cardiac vs infectious etiologies for their pulmonary findings. We conducted a retrospective ...