AIMC Topic: Infant

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Research on Infant Health Diagnosis and Intelligence Development Based on Machine Learning and Health Information Statistics.

Frontiers in public health
Intelligent health diagnosis for young children aims at maintaining and promoting the healthy development of young children, aiming to make young children have a healthy state and provide a better future for their physical and mental health developme...

Development and Validation of a Deep Learning Model to Predict the Occurrence and Severity of Retinopathy of Prematurity.

JAMA network open
IMPORTANCE: Retinopathy of prematurity (ROP) is the leading cause of childhood blindness worldwide. Prediction of ROP before onset holds great promise for reducing the risk of blindness.

Machine learning for understanding and predicting neurodevelopmental outcomes in premature infants: a systematic review.

Pediatric research
BACKGROUND: Machine learning has been attracting increasing attention for use in healthcare applications, including neonatal medicine. One application for this tool is in understanding and predicting neurodevelopmental outcomes in preterm infants. In...

Hybrid HCNN-KNN Model Enhances Age Estimation Accuracy in Orthopantomography.

Frontiers in public health
Age estimation in dental radiographs Orthopantomography (OPG) is a medical imaging technique that physicians and pathologists utilize for disease identification and legal matters. For example, for estimating post-mortem interval, detecting child abus...

Improvements for Therapeutic Intervention from the Use of Web Applications and Machine Learning Techniques in Different Affectations in Children Aged 0-6 Years.

International journal of environmental research and public health
Technological advances together with machine learning techniques give health science disciplines tools that can improve the accuracy of evaluation and diagnosis. The objectives of this study were: (1) to design a web application based on cloud techno...

Predicting risks of low birth weight in Bangladesh with machine learning.

PloS one
BACKGROUND AND OBJECTIVE: Low birth weight is one of the primary causes of child mortality and several diseases of future life in developing countries, especially in Southern Asia. The main objective of this study is to determine the risk factors of ...

Modified technique for robot-assisted laparoscopic infantile ureteral reimplantation for obstructive megaureter.

Journal of pediatric surgery
PURPOSE: To describe a novel modification of technique to improve efficacy of robot-assisted laparoscopic extravesical ureteral reimplantation (RALUR-EV) in infants.

Deep Learning for Infant Cry Recognition.

International journal of environmental research and public health
Recognizing why an infant cries is challenging as babies cannot communicate verbally with others to express their wishes or needs. This leads to difficulties for parents in identifying the needs and the health of their infants. This study used deep l...

NeoAI 1.0: Machine learning-based paradigm for prediction of neonatal and infant risk of death.

Computers in biology and medicine
BACKGROUND: The Neonatal mortality rate in the United States is 3.8 deaths per 1000 live births, which is comparably higher than other nations.