AIMC Topic: Infant
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Realistic 3D infant head surfaces augmentation to improve AI-based diagnosis of cranial deformities.
Journal of biomedical informatics
Jun 22, 2022
Evaluation of the head shape of newborns is needed to detect cranial deformities, disturbances in head growth, and consequently, to predict short- and long-term neurodevelopment. Currently, there is a lack of automatic tools to provide a detailed eva...
Explainable deep learning algorithm for distinguishing incomplete Kawasaki disease by coronary artery lesions on echocardiographic imaging.
Computer methods and programs in biomedicine
Jun 21, 2022
BACKGROUND AND OBJECTIVE: Incomplete Kawasaki disease (KD) has often been misdiagnosed due to a lack of the clinical manifestations of classic KD. However, it is associated with a markedly higher prevalence of coronary artery lesions. Identifying cor...
Heart age estimated using explainable advanced electrocardiography.
Scientific reports
Jun 14, 2022
Electrocardiographic (ECG) Heart Age conveying cardiovascular risk has been estimated by both Bayesian and artificial intelligence approaches. We hypothesised that explainable measures from the 10-s 12-lead ECG could successfully predict Bayesian 5-m...
Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review.
Sensors (Basel, Switzerland)
Jun 9, 2022
Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential ...
Research on Infant Health Diagnosis and Intelligence Development Based on Machine Learning and Health Information Statistics.
Frontiers in public health
Jun 2, 2022
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 Screen for Trisomy 21 During the First Trimester From Nuchal Ultrasonographic Images.
JAMA network open
Jun 1, 2022
IMPORTANCE: Accurate screening of trisomy 21 in the first trimester can provide an early opportunity for decision-making regarding reproductive choices.
Development and Validation of a Deep Learning Model to Predict the Occurrence and Severity of Retinopathy of Prematurity.
JAMA network open
Jun 1, 2022
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
May 31, 2022
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
May 30, 2022
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
May 27, 2022
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...
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