AI Medical Compendium Topic:
Child

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Pediatric cardiac surgery: machine learning models for postoperative complication prediction.

Journal of anesthesia
PURPOSE: Managing children undergoing cardiac surgery with cardiopulmonary bypass (CPB) presents a significant challenge for anesthesiologists. Machine Learning (ML)-assisted tools have the potential to enhance the recognition of patients at risk of ...

Information extraction from medical case reports using OpenAI InstructGPT.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Researchers commonly use automated solutions such as Natural Language Processing (NLP) systems to extract clinical information from large volumes of unstructured data. However, clinical text's poor semantic structure and dom...

A preliminary prediction model of pediatric Mycoplasma pneumoniae pneumonia based on routine blood parameters by using machine learning method.

BMC infectious diseases
BACKGROUND: The prevalence and severity of pediatric Mycoplasma pneumoniae pneumonia (MPP) poses a significant threat to the health and lives of children. In this study, we aim to systematically evaluate the value of routine blood parameters in predi...

The role of morphometric characteristics in predicting 20-meter sprint performance through machine learning.

Scientific reports
The aim of this study was to test the morphometric features affecting 20-m sprint performance in children at the first level of primary education using machine learning (ML) algorithms. In this study, 130 male and 152 female volunteers aged between 6...

Deep learning with convolution neural network detecting mesiodens on panoramic radiographs: comparing four models.

Odontology
The aim of this study was to develop an optimal, simple, and lightweight deep learning convolutional neural network (CNN) model to detect the presence of mesiodens on panoramic radiographs. A total of 628 panoramic radiographs with and without mesiod...

Diagnostic performance of an AI algorithm for the detection of appendicular bone fractures in pediatric patients.

European journal of radiology
PURPOSE: To evaluate the diagnostic performance of an Artificial Intelligence (AI) algorithm, previously trained using both adult and pediatric patients, for the detection of acute appendicular fractures in the pediatric population on conventional X-...

Accelerated cardiac magnetic resonance imaging using deep learning for volumetric assessment in children.

Pediatric radiology
BACKGROUND: Ventricular volumetry using a short-axis stack of two-dimensional (D) cine balanced steady-state free precession (bSSFP) sequences is crucial in any cardiac magnetic resonance imaging (MRI) examination. This task becomes particularly chal...

The emerging paradigm in pediatric rheumatology: harnessing the power of artificial intelligence.

Rheumatology international
Artificial intelligence algorithms, with roots extending into the past but experiencing a resurgence and evolution in recent years due to their superiority over traditional methods and contributions to human capabilities, have begun to make their pre...

Integrating Artificial Intelligence Into the Visualization and Modeling of Three-Dimensional Anatomy in Pediatric Surgical Patients.

Journal of pediatric surgery
BACKGROUND: Pediatric surgeons often treat patients with complex anatomical considerations due to congenital anomalies or distortion of normal structures by solid organ tumors. There are multiple applications for three-dimensional visualization of th...

Accuracy of automated forensic dental age estimation lab (F-DentEst Lab) on large Malaysian dataset.

Forensic science international
When a disaster occurs, the authority must prioritise two things. First, the search and rescue of lives, and second, the identification and management of deceased individuals. However, with thousands of dead bodies to be individually identified in ma...