AIMC Topic: Infant

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Machine-learning-based diagnostics of EEG pathology.

NeuroImage
Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted features), and end-to-end approaches (with learned features). Previous studies on EEG pathology decoding ...

Deep Learning for Improved Risk Prediction in Surgical Outcomes.

Scientific reports
The Norwood surgical procedure restores functional systemic circulation in neonatal patients with single ventricle congenital heart defects, but this complex procedure carries a high mortality rate. In this study we address the need to provide an acc...

Real-time Inference and Detection of Disruptive EEG Networks for Epileptic Seizures.

Scientific reports
Recent studies in brain science and neurological medicine paid a particular attention to develop machine learning-based techniques for the detection and prediction of epileptic seizures with electroencephalogram (EEG). As a noninvasive monitoring met...

A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type.

PLoS computational biology
The microbiome is a new frontier for building predictors of human phenotypes. However, machine learning in the microbiome is fraught with issues of reproducibility, driven in large part by the wide range of analytic models and metagenomic data types ...

Prediction of chronological and biological age from laboratory data.

Aging
Aging has pronounced effects on blood laboratory biomarkers used in the clinic. Prior studies have largely investigated one biomarker or population at a time, limiting a comprehensive view of biomarker variation and aging across different populations...

Deeply Learned Classifiers for Age and Gender Predictions of Unfiltered Faces.

TheScientificWorldJournal
Age and gender predictions of unfiltered faces classify unconstrained real-world facial images into predefined age and gender. Significant improvements have been made in this research area due to its usefulness in intelligent real-world applications....

Identification of the Facial Features of Patients With Cancer: A Deep Learning-Based Pilot Study.

Journal of medical Internet research
BACKGROUND: Cancer has become the second leading cause of death globally. Most cancer cases are due to genetic mutations, which affect metabolism and result in facial changes.