AIMC Topic: Infant, Newborn

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Deep-Learning-Driven Quantification of Interstitial Fibrosis in Digitized Kidney Biopsies.

The American journal of pathology
Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA ...

[Main biological tools applied to newborn screening: Landscape and future perspectives].

Medecine sciences : M/S
Over the past fifty years, neonatal screening has become essential in the public health programs of a large number of countries. During all these years, the number of detectable diseases has continued to grow, following the possibilities offered by t...

Data-level Linkage of Multiple Surveys for Improved Understanding of Global Health Challenges.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Data-driven approaches can provide more enhanced insights for domain experts in addressing critical global health challenges, such as newborn and child health, using surveys (e.g., Demographic Health Survey). Though there are multiple surveys on the ...

A Hybrid DCNN-SVM Model for Classifying Neonatal Sleep and Wake States Based on Facial Expressions in Video.

IEEE journal of biomedical and health informatics
Sleep is a natural phenomenon controlled by the central nervous system. The sleep-wake pattern, which functions as an essential indicator of neurophysiological organization in the neonatal period, has profound meaning in the prediction of cognitive d...

Preterm Newborn Presence Detection in Incubator and Open Bed Using Deep Transfer Learning.

IEEE journal of biomedical and health informatics
Video-based motion analysis recently appeared to be a promising approach in neonatal intensive care units for monitoring the state of preterm newborns since it is contact-less and noninvasive. However it is important to remove periods when the newbor...

Novel AI driven approach to classify infant motor functions.

Scientific reports
The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the classic Prechtl general movements assessment (GMA)...

A Zwitterionic-Aromatic Motif-Based ionic skin for highly biocompatible and Glucose-Responsive sensor.

Journal of colloid and interface science
Electronic skins that can sense external stimuli have been of great significance in artificial intelligence and smart wearable devices in recent years. However, most of current skin materials are unable to achieve high biocompatibility and anti-bacte...

Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

International journal of laboratory hematology
INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains difficult due to complex pathogenesis and presentation. We created a machine learning model for bacteria...

Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.

JAMA network open
IMPORTANCE: A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of RO...

Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The number of deaths from COVID-19 continues to surge worldwide. In particular, if a patient's condition is sufficiently severe to require invasive ventilation, it is more likely to lead to death than to recovery.