AIMC Topic: Child

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Chronic cholestasis detection by a novel tool: automated analysis of cytokeratin 7-stained liver specimens.

Diagnostic pathology
BACKGROUND: The objective was to build a novel method for automated image analysis to locate and quantify the number of cytokeratin 7 (K7)-positive hepatocytes reflecting cholestasis by applying deep learning neural networks (AI model) in a cohort of...

Deep reasoning neural network analysis to predict language deficits from psychometry-driven DWI connectome of young children with persistent language concerns.

Human brain mapping
This study investigated whether current state-of-the-art deep reasoning network analysis on psychometry-driven diffusion tractography connectome can accurately predict expressive and receptive language scores in a cohort of young children with persis...

Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones.

Seizure
OBJECTIVE: One barrier hindering high frequency brain signals (HFBS, >80 Hz) from wide clinical applications is that the brain generates both pathological and physiological HFBS. This study was to find specific biomarkers for localizing epileptogenic...

Diagnosing Atrial Septal Defect from Electrocardiogram with Deep Learning.

Pediatric cardiology
The heart murmur associated with atrial septal defects is often faint and can thus only be detected by chance. Although electrocardiogram examination can prompt diagnoses, identification of specific findings remains a major challenge. We demonstrate ...

Machine learning to reveal an astute risk predictive framework for Gynecologic Cancer and its impact on women psychology: Bangladeshi perspective.

BMC bioinformatics
BACKGROUND: In this research, an astute system has been developed by using machine learning and data mining approach to predict the risk level of cervical and ovarian cancer in association to stress.

Assessing Children's Fine Motor Skills With Sensor-Augmented Toys: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Approximately 5%-10% of elementary school children show delayed development of fine motor skills. To address these problems, detection is required. Current assessment tools are time-consuming, require a trained supervisor, and are not mot...

Robot-assisted anorectal pull-through for anorectal malformations with rectourethral and rectovesical fistula: feasibility and short-term outcome.

Surgical endoscopy
BACKGROUND: Multiple structures in the anorectal area are closely related to defecation, voiding and sexual function. Although laparoscopic-assisted anorectal pull-through is widely accepted as a minimally invasive surgical technique, controversy sti...

Prediction of causative genes in inherited retinal disorder from fundus photography and autofluorescence imaging using deep learning techniques.

The British journal of ophthalmology
BACKGROUND/AIMS: To investigate the utility of a data-driven deep learning approach in patients with inherited retinal disorder (IRD) and to predict the causative genes based on fundus photography and fundus autofluorescence (FAF) imaging.

Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The number of deaths from COVID-19 continues to surge worldwide. In particular, if a patient's condition is sufficiently severe to require invasive ventilation, it is more likely to lead to death than to recovery.