AIMC Topic: Infant
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Machine learning-based prediction of critical illness in children visiting the emergency department.
PloS one
Feb 17, 2022
OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have ...
With or without human interference for precise age estimation based on machine learning?
International journal of legal medicine
Feb 14, 2022
Age estimation can aid in forensic medicine applications, diagnosis, and treatment planning for orthodontics and pediatrics. Existing dental age estimation methods rely heavily on specialized knowledge and are highly subjective, wasting time, and ene...
Convolutional mesh autoencoders for the 3-dimensional identification of FGFR-related craniosynostosis.
Scientific reports
Feb 9, 2022
Clinical diagnosis of craniofacial anomalies requires expert knowledge. Recent studies have shown that artificial intelligence (AI) based facial analysis can match the diagnostic capabilities of expert clinicians in syndrome identification. In genera...
A neuromorphic spiking neural network detects epileptic high frequency oscillations in the scalp EEG.
Scientific reports
Feb 2, 2022
Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This development has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The deman...
Humans
Wearable Electronic Devices
Artifacts
Neural Networks, Computer
Treatment Outcome
Brain Waves
Reproducibility of Results
Time Factors
Brain
Drug Resistant Epilepsy
Male
Predictive Value of Tests
Female
Child, Preschool
Epilepsies, Partial
Electroencephalography
Infant
Child
Signal Processing, Computer-Assisted
Adolescent
Frameless robot-assisted stereotactic biopsies for lesions of the brainstem-a series of 103 consecutive biopsies.
Journal of neuro-oncology
Jan 27, 2022
PURPOSE: Targeted treatment for brainstem lesions requires above all a precise histopathological and molecular diagnosis. In the current technological era, robot-assisted stereotactic biopsies represent an accurate and safe procedure for tissue diagn...
DNA Methylation Biomarkers-Based Human Age Prediction Using Machine Learning.
Computational intelligence and neuroscience
Jan 24, 2022
PURPOSE: Age can be an important clue in uncovering the identity of persons that left biological evidence at crime scenes. With the availability of DNA methylation data, several age prediction models are developed by using statistical and machine lea...
Assessment of germinal matrix hemorrhage on head ultrasound with deep learning algorithms.
Pediatric radiology
Jan 22, 2022
BACKGROUND: Germinal matrix hemorrhage-intraventricular hemorrhage is among the most common intracranial complications in premature infants. Early detection is important to guide clinical management for improved patient prognosis.
Laparoscopic and robotic pyeloplasty as minimally invasive alternatives to the open approach for the treatment of uretero-pelvic junction obstruction in infants: a multi-institutional comparison of outcomes and learning curves.
World journal of urology
Jan 19, 2022
BACKGROUND: Since the development of minimally invasive surgery (MIS), laparoscopic and robotic approaches have been widely adopted. However, little has been published detailing the learning curve of MIS, especially in infants.
Evaluation of Maturation in Preterm Infants Through an Ensemble Machine Learning Algorithm Using Physiological Signals.
IEEE journal of biomedical and health informatics
Jan 17, 2022
This study was designed to test if heart rate variability (HRV) data from preterm and full-term infants could be used to estimate their functional maturational age (FMA), using a machine learning model. We propose that the FMA, and its deviation from...
Using Machine Learning to Identify Metabolomic Signatures of Pediatric Chronic Kidney Disease Etiology.
Journal of the American Society of Nephrology : JASN
Jan 11, 2022
BACKGROUND: Untargeted plasma metabolomic profiling combined with machine learning (ML) may lead to discovery of metabolic profiles that inform our understanding of pediatric CKD causes. We sought to identify metabolomic signatures in pediatric CKD b...
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