Deep Learning-Based Detection of the Acute Respiratory Distress Syndrome: What Are the Models Learning?

Autor: Rehm, Gregory B., Wang, Chao, Cortes-Puch, Irene, Chuah, Chen-Nee, Adams, Jason

The acute respiratory distress syndrome (ARDS) is a severe form of hypoxemic respiratory failure with in-hospital mortality of 35-46%. High mortality is thought to be related in part to challenges in making a prompt diagnosis, which may in turn delay

Externí odkaz: http://arxiv.org/abs/2109.12323

Improving Mechanical Ventilator Clinical Decision Support Systems with A Machine Learning Classifier for Determining Ventilator Mode

Autor: Rehm, Gregory B., Kuhn, Brooks T., Nguyen, Jimmy, Anderson, Nicholas R., Chuah, Chen-Nee, Adams, Jason Y.

Clinical decision support systems (CDSS) will play an in-creasing role in improving the quality of medical care for critically ill patients. However, due to limitations in current informatics infrastructure, CDSS do not always have com-plete informat

Externí odkaz: http://arxiv.org/abs/1904.12969

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Use of Machine Learning to Screen for Acute Respiratory Distress Syndrome Using Raw Ventilator Waveform Data.

Autor: Rehm GB; Department of Computer Science, University of California Davis, Davis, CA., Cortés-Puch I; Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of California Davis, Sacramento, CA., Kuhn BT; Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of California Davis, Sacramento, CA., Nguyen J; Department of Respiratory Care, University of California Davis Health, Sacramento, CA., Fazio SA; Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of California Davis, Sacramento, CA., Johnson MA; Department of Emergency Medicine, University of Utah, Salt Lake City, UT., Anderson NR; Division of Informatics, Department of Public Health Sciences, University of California Davis, Davis, CA., Chuah CN; Department of Electrical and Computer Engineering, University of California Davis, Davis, CA., Adams JY; Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of California Davis, Sacramento, CA.

Publikováno v: Critical care explorations [Crit Care Explor] 2021 Jan 08; Vol. 3 (1), pp. e0313. Date of Electronic Publication: 2021 Jan 08 (Print Publication: 2021).