AIMC Topic: Child

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Submillimeter MR fingerprinting using deep learning-based tissue quantification.

Magnetic resonance in medicine
PURPOSE: To develop a rapid 2D MR fingerprinting technique with a submillimeter in-plane resolution using a deep learning-based tissue quantification approach.

Endoscopic-assisted robotic pyelolithotomy: a viable treatment option for complex pediatric nephrolithiasis.

Journal of pediatric urology
INTRODUCTION AND OBJECTIVE: Endourological and percutaneous approaches are the standard of care for treatment of pediatric urolithiasis. However, in certain situations, an endoscopic-assisted robotic pyelolithotomy (EARP) can be an acceptable alterna...

Conflict management in the fusion of complementary segmentations of deformed kidneys and nephroblastoma.

Medical image analysis
The fusion of multiple segmentations aims to improve their accuracy in order to make them exploitable. However, conflicts may appear. In this paper, two conflict-management models are proposed for the fusion of complementary segmentations. This confl...

Data-Driven Diagnostics and the Potential of Mobile Artificial Intelligence for Digital Therapeutic Phenotyping in Computational Psychiatry.

Biological psychiatry. Cognitive neuroscience and neuroimaging
Data science and digital technologies have the potential to transform diagnostic classification. Digital technologies enable the collection of big data, and advances in machine learning and artificial intelligence enable scalable, rapid, and automate...

Deep learning segmentation of orbital fat to calibrate conventional MRI for longitudinal studies.

NeuroImage
In conventional non-quantitative magnetic resonance imaging, image contrast is consistent within images, but absolute intensity can vary arbitrarily between scans. For quantitative analysis of intensity data, images are typically normalized to a cons...

Characterizing autism spectrum disorder by deep learning spontaneous brain activity from functional near-infrared spectroscopy.

Journal of neuroscience methods
BACKGROUND: Functional near-infrared spectroscopy (fNIRS) was used to investigate spontaneous hemodynamic fluctuations in the bilateral temporal cortices for typically developing (TD) children and children with autism spectrum disorder (ASD).

Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery.

Epilepsia
OBJECTIVE: Delay to resective epilepsy surgery results in avoidable disease burden and increased risk of mortality. The objective was to prospectively validate a natural language processing (NLP) application that uses provider notes to assign epileps...

Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.

Journal of cutaneous pathology
PURPOSE: Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which ...

[Hemoglobinuria in children hospitalized in Ouagadougou: short term inpatient care and prognosis].

The Pan African medical journal
INTRODUCTION: The purpose of this study was to analyze the epidemiological, diagnostic, therapeutic and evolutionary features of hemoglobinuria in children hospitalized in the Pediatric University Hospital Charles de Gaulle, Ouagadougou.

Deep Learning for Lesion Detection, Progression, and Prediction of Musculoskeletal Disease.

Journal of magnetic resonance imaging : JMRI
Deep learning is one of the most exciting new areas in medical imaging. This review article provides a summary of the current clinical applications of deep learning for lesion detection, progression, and prediction of musculoskeletal disease on radio...