AIMC Topic: Sudden Infant Death
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Machine Learning Approaches to Determine Feature Importance for Predicting Infant Autopsy Outcome.
Pediatric and developmental pathology : the official journal of the Society for Pediatric Pathology and the Paediatric Pathology Society
Mar 30, 2021
INTRODUCTION: Sudden unexpected death in infancy (SUDI) represents the commonest presentation of postneonatal death. We explored whether machine learning could be used to derive data driven insights for prediction of infant autopsy outcome.
Integrative Analysis of Proteomics Data to Obtain Clinically Relevant Markers.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2018
The analysis of proteomics data can be significantly challenging. Beyond the technical challenges of accurately identifying and quantifying peptides, identifying the most biologically coherent set of biomarkers can be a particularly daunting step. In...
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