AI Medical Compendium Topic:
Child, Preschool

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Predicting age at onset of type 1 diabetes in children using regression, artificial neural network and Random Forest: A case study in Saudi Arabia.

PloS one
The rising incidence of type 1 diabetes (T1D) among children is an increasing concern globally. A reliable estimate of the age at onset of T1D in children would facilitate intervention plans for medical practitioners to reduce the problems with delay...

Radiation Dose Reduction for 80-kVp Pediatric CT Using Deep Learning-Based Reconstruction: A Clinical and Phantom Study.

AJR. American journal of roentgenology
Deep learning-based reconstruction (DLR) may facilitate CT radiation dose reduction, but a paucity of literature has compared lower-dose DLR images with standard-dose iterative reconstruction (IR) images or explored application of DLR to low-tube-vo...

Machine learning-based prediction of critical illness in children visiting the emergency department.

PloS one
OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have ...

Artificial Intelligence Technology-Based Medical Information Processing and Emergency First Aid Nursing Management.

Computational and mathematical methods in medicine
This study was aimed at exploring the new management mode of medical information processing and emergency first aid nursing management under the new artificial intelligence technology. This study will use the artificial intelligence algorithm to opti...

A neuromorphic spiking neural network detects epileptic high frequency oscillations in the scalp EEG.

Scientific reports
Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This development has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The deman...

A Machine-Learning Model for Lung Age Forecasting by Analyzing Exhalations.

Sensors (Basel, Switzerland)
Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. R...

Frameless robot-assisted stereotactic biopsies for lesions of the brainstem-a series of 103 consecutive biopsies.

Journal of neuro-oncology
PURPOSE: Targeted treatment for brainstem lesions requires above all a precise histopathological and molecular diagnosis. In the current technological era, robot-assisted stereotactic biopsies represent an accurate and safe procedure for tissue diagn...

External validation of deep learning-based bone-age software: a preliminary study with real world data.

Scientific reports
Artificial intelligence (AI) is increasingly being used in bone-age (BA) assessment due to its complicated and lengthy nature. We aimed to evaluate the clinical performance of a commercially available deep learning (DL)-based software for BA assessme...

DNA Methylation Biomarkers-Based Human Age Prediction Using Machine Learning.

Computational intelligence and neuroscience
PURPOSE: Age can be an important clue in uncovering the identity of persons that left biological evidence at crime scenes. With the availability of DNA methylation data, several age prediction models are developed by using statistical and machine lea...

Denoising of pediatric low dose abdominal CT using deep learning based algorithm.

PloS one
OBJECTIVES: To evaluate standard dose-like computed tomography (CT) images generated by a deep learning method, trained using unpaired low-dose CT (LDCT) and standard-dose CT (SDCT) images.