AI Medical Compendium Topic:
Infant

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Practical implementation of artificial intelligence algorithms in pulmonary auscultation examination.

European journal of pediatrics
Lung auscultation is an important part of a physical examination. However, its biggest drawback is its subjectivity. The results depend on the experience and ability of the doctor to perceive and distinguish pathologies in sounds heard via a stethosc...

Intelligent Labeling Based on Fisher Information for Medical Image Segmentation Using Deep Learning.

IEEE transactions on medical imaging
Deep convolutional neural networks (CNN) have recently achieved superior performance at the task of medical image segmentation compared to classic models. However, training a generalizable CNN requires a large amount of training data, which is diffic...

An Efficient Deep Learning Approach to Pneumonia Classification in Healthcare.

Journal of healthcare engineering
This study proposes a convolutional neural network model trained from scratch to classify and detect the presence of pneumonia from a collection of chest X-ray image samples. Unlike other methods that rely solely on transfer learning approaches or tr...

Biochemical, machine learning and molecular approaches for the differential diagnosis of Mucopolysaccharidoses.

Molecular and cellular biochemistry
This study was aimed to construct classification and regression tree (CART) model of glycosaminoglycans (GAGs) for the differential diagnosis of Mucopolysaccharidoses (MPS). Two-dimensional electrophoresis and liquid chromatography-tandem mass spectr...

Prediction of cervical spine injury in young pediatric patients: an optimal trees artificial intelligence approach.

Journal of pediatric surgery
BACKGROUND: Cervical spine injuries (CSI) are a major concern in young pediatric trauma patients. The consequences of missed injuries and difficulties in injury clearance for non-verbal patients have led to a tendency to image young children. Imaging...

Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data.

PloS one
BACKGROUND: Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data...

Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence.

Nature medicine
Artificial intelligence (AI)-based methods have emerged as powerful tools to transform medical care. Although machine learning classifiers (MLCs) have already demonstrated strong performance in image-based diagnoses, analysis of diverse and massive e...

Prediction of mortality following pediatric heart transplant using machine learning algorithms.

Pediatric transplantation
BACKGROUND: Optimizing transplant candidates' priority for donor organs depends on the accurate assessment of post-transplant outcomes. Due to the complexity of transplantation and the wide range of possible serious complications, recipient outcomes ...

Predicting Hemodynamic Shock from Thermal Images using Machine Learning.

Scientific reports
Proactive detection of hemodynamic shock can prevent organ failure and save lives. Thermal imaging is a non-invasive, non-contact modality to capture body surface temperature with the potential to reveal underlying perfusion disturbance in shock. In ...

Machine Learning Models for Genetic Risk Assessment of Infants with Non-syndromic Orofacial Cleft.

Genomics, proteomics & bioinformatics
The isolated type of orofacial cleft, termed non-syndromic cleft lip with or without cleft palate (NSCL/P), is the second most common birth defect in China, with Asians having the highest incidence in the world. NSCL/P involves multiple genes and com...