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feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
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feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
primary data » primary care (Expand Search)
data feature » data figure (Expand Search), each feature (Expand Search), a feature (Expand Search)
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181
Image_2_Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning.PDF
Published 2021“…<p>Background: High flow nasal cannula (HFNC) is commonly used as non-invasive respiratory support in critically ill children. There are limited data to inform consensus on optimal device parameters, determinants of successful patient response, and indications for escalation of support. …”
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182
Image_6_Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning.PDF
Published 2021“…<p>Background: High flow nasal cannula (HFNC) is commonly used as non-invasive respiratory support in critically ill children. There are limited data to inform consensus on optimal device parameters, determinants of successful patient response, and indications for escalation of support. …”
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183
Table_2_Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning.docx
Published 2021“…<p>Background: High flow nasal cannula (HFNC) is commonly used as non-invasive respiratory support in critically ill children. There are limited data to inform consensus on optimal device parameters, determinants of successful patient response, and indications for escalation of support. …”
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184
Image_4_Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning.PDF
Published 2021“…<p>Background: High flow nasal cannula (HFNC) is commonly used as non-invasive respiratory support in critically ill children. There are limited data to inform consensus on optimal device parameters, determinants of successful patient response, and indications for escalation of support. …”