FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2912962075> ?p ?o ?g. }

• W2912962075 endingPage "12" @default.
• W2912962075 startingPage "1" @default.
• W2912962075 abstract "Background and Objective : The emergence of the nonnutritive suck (NNS) pattern in preterm infants reflects the integrity of the brain and is used by clinicians in the neonatal intensive care unit (NICU) to assess feeding readiness and oromotor development. A critical need exists for an integrated software platform that provides NNS signal preprocessing, adaptive waveform discrimination, feature detection, and batch processing of big data sets across multiple NICU sites. Thus, the goal was to develop and describe a cross-platform graphical user interface (GUI) and terminal application known as NeoNNS for single and batch file time series and frequency-domain analyses of NNS compression pressure waveforms using analysis parameters derived from previous research on NNS dynamics. Methods . NeoNNS was implemented with Python and the Tkinter GUI package. The NNS signal-processing pipeline included a low-pass filter, asymmetric regression baseline correction, NNS peak detection, and NNS burst classification. Data visualizations and parametric analyses included time- and frequency-domain view, NNS spatiotemporal index view, and feature cluster analysis to model oral feeding readiness. Results . 568 suck assessment files sampled from 30 extremely preterm infants were processed in the batch mode (<50 minutes) to generate time- and frequency-domain analyses of infant NNS pressure waveform data. NNS cycle discrimination and NNS burst classification yield quantification of NNS waveform features as a function of postmenstrual age. Hierarchical cluster analysis (based on the Tsfresh python package and NeoNNS) revealed the capability to label NNS records for feeding readiness. Conclusions . NeoNNS provides a versatile software platform to rapidly quantify the dynamics of NNS development in time and frequency domains at cribside over repeated sessions for an individual baby or among large numbers of preterm infants at multiple hospital sites to support big data analytics. The hierarchical cluster feature analysis facilitates modeling of feeding readiness based on quantitative features of the NNS compression pressure waveform." @default.
• W2912962075 created "2019-02-21" @default.
• W2912962075 creator A5012190254 @default.
• W2912962075 creator A5014404747 @default.
• W2912962075 creator A5071301224 @default.
• W2912962075 creator A5074669569 @default.
• W2912962075 creator A5082596932 @default.
• W2912962075 date "2019-02-04" @default.
• W2912962075 modified "2023-10-16" @default.
• W2912962075 title "Automatic Nonnutritive Suck Waveform Discrimination and Feature Extraction in Preterm Infants" @default.
• W2912962075 cites W1591684888 @default.
• W2912962075 cites W1596515083 @default.
• W2912962075 cites W1975767442 @default.
• W2912962075 cites W1981209142 @default.
• W2912962075 cites W1982842953 @default.
• W2912962075 cites W1983870611 @default.
• W2912962075 cites W2005030163 @default.
• W2912962075 cites W2011484430 @default.
• W2912962075 cites W2016151298 @default.
• W2912962075 cites W2016240929 @default.
• W2912962075 cites W2023185858 @default.
• W2912962075 cites W2027278235 @default.
• W2912962075 cites W2042882626 @default.
• W2912962075 cites W2064302606 @default.
• W2912962075 cites W2072333982 @default.
• W2912962075 cites W2077381297 @default.
• W2912962075 cites W2083313245 @default.
• W2912962075 cites W2088975312 @default.
• W2912962075 cites W2090097983 @default.
• W2912962075 cites W2092880482 @default.
• W2912962075 cites W2100739027 @default.
• W2912962075 cites W2120448031 @default.
• W2912962075 cites W2126140809 @default.
• W2912962075 cites W2129636921 @default.
• W2912962075 cites W2132374301 @default.
• W2912962075 cites W2140160167 @default.
• W2912962075 cites W2140327452 @default.
• W2912962075 cites W2149790616 @default.
• W2912962075 cites W2163691126 @default.
• W2912962075 cites W2473352665 @default.
• W2912962075 cites W2625110220 @default.
• W2912962075 cites W2919135175 @default.
• W2912962075 cites W4206029558 @default.
• W2912962075 cites W4231591793 @default.
• W2912962075 cites W4253293211 @default.
• W2912962075 cites W45490721 @default.
• W2912962075 cites W979425508 @default.
• W2912962075 doi "https://doi.org/10.1155/2019/7496591" @default.
• W2912962075 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6378788" @default.
• W2912962075 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30863456" @default.
• W2912962075 hasPublicationYear "2019" @default.
• W2912962075 type Work @default.
• W2912962075 sameAs 2912962075 @default.
• W2912962075 citedByCount "5" @default.
• W2912962075 countsByYear W29129620752019 @default.
• W2912962075 countsByYear W29129620752020 @default.
• W2912962075 countsByYear W29129620752021 @default.
• W2912962075 countsByYear W29129620752022 @default.
• W2912962075 crossrefType "journal-article" @default.
• W2912962075 hasAuthorship W2912962075A5012190254 @default.
• W2912962075 hasAuthorship W2912962075A5014404747 @default.
• W2912962075 hasAuthorship W2912962075A5071301224 @default.
• W2912962075 hasAuthorship W2912962075A5074669569 @default.
• W2912962075 hasAuthorship W2912962075A5082596932 @default.
• W2912962075 hasBestOaLocation W29129620751 @default.
• W2912962075 hasConcept C111919701 @default.
• W2912962075 hasConcept C124101348 @default.
• W2912962075 hasConcept C153180895 @default.
• W2912962075 hasConcept C154945302 @default.
• W2912962075 hasConcept C197424946 @default.
• W2912962075 hasConcept C34736171 @default.
• W2912962075 hasConcept C41008148 @default.
• W2912962075 hasConcept C519991488 @default.
• W2912962075 hasConcept C554190296 @default.
• W2912962075 hasConcept C76155785 @default.
• W2912962075 hasConceptScore W2912962075C111919701 @default.
• W2912962075 hasConceptScore W2912962075C124101348 @default.
• W2912962075 hasConceptScore W2912962075C153180895 @default.
• W2912962075 hasConceptScore W2912962075C154945302 @default.
• W2912962075 hasConceptScore W2912962075C197424946 @default.
• W2912962075 hasConceptScore W2912962075C34736171 @default.
• W2912962075 hasConceptScore W2912962075C41008148 @default.
• W2912962075 hasConceptScore W2912962075C519991488 @default.
• W2912962075 hasConceptScore W2912962075C554190296 @default.
• W2912962075 hasConceptScore W2912962075C76155785 @default.
• W2912962075 hasFunder F4320332161 @default.
• W2912962075 hasLocation W29129620751 @default.
• W2912962075 hasLocation W29129620752 @default.
• W2912962075 hasLocation W29129620753 @default.
• W2912962075 hasLocation W29129620754 @default.
• W2912962075 hasLocation W29129620755 @default.
• W2912962075 hasLocation W29129620756 @default.
• W2912962075 hasOpenAccess W2912962075 @default.
• W2912962075 hasPrimaryLocation W29129620751 @default.
• W2912962075 hasRelatedWork W1699080303 @default.
• W2912962075 hasRelatedWork W1974895211 @default.
• W2912962075 hasRelatedWork W2897624483 @default.
• W2912962075 hasRelatedWork W3116064965 @default.

• next