AIMC Topic: Child

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Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique.

European radiology
OBJECTIVES: To evaluate the image quality of low iodine concentration, dual-energy CT (DECT) combined with a deep learning-based noise reduction technique for pediatric abdominal CT, compared with standard iodine concentration single-energy polychrom...

Automatic segmentation, classification, and follow-up of optic pathway gliomas using deep learning and fuzzy c-means clustering based on MRI.

Medical physics
PURPOSE: Optic pathway gliomas (OPG) are low-grade pilocytic astrocytomas accounting for 3-5% of pediatric intracranial tumors. Accurate and quantitative follow-up of OPG using magnetic resonance imaging (MRI) is crucial for therapeutic decision maki...

A qualitative research framework for the design of user-centered displays of explanations for machine learning model predictions in healthcare.

BMC medical informatics and decision making
BACKGROUND: There is an increasing interest in clinical prediction tools that can achieve high prediction accuracy and provide explanations of the factors leading to increased risk of adverse outcomes. However, approaches to explaining complex machin...

BrainNET: Inference of Brain Network Topology Using Machine Learning.

Brain connectivity
To develop a new functional magnetic resonance image (fMRI) network inference method, BrainNET, that utilizes an efficient machine learning algorithm to quantify contributions of various regions of interests (ROIs) in the brain to a specific ROI. B...

Deep learning-enabled MRI-only photon and proton therapy treatment planning for paediatric abdominal tumours.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To assess the feasibility of magnetic resonance imaging (MRI)-only treatment planning for photon and proton radiotherapy in children with abdominal tumours.

Acceptance of patients towards task-autonomous robotic cochlear implantation: An exploratory study.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Recently, task-autonomous image-guided robotic cochlear implantation has been successfully completed in patients. However, no data exist on patients' perspective of this new technology. The aim of this study was to evaluate the acceptance...

Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature.

Journal of clinical research in pediatric endocrinology
Assessment and management of children with growth failure has improved greatly over recent years. However, there remains a strong potential for further improvements by using novel digital techniques. A panel of experts discussed developments in digit...

Artificial intelligence accuracy in detecting pathological breath sounds in children using digital stethoscopes.

Respiratory research
BACKGROUND: Manual auscultation to detect abnormal breath sounds has poor inter-observer reliability. Digital stethoscopes with artificial intelligence (AI) could improve reliable detection of these sounds. We aimed to independently test the abilitie...

Bone age assessment based on deep convolution neural network incorporated with segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Bone age assessment is not only an important means of assessing maturity of adolescents, but also plays an indispensable role in the fields of orthodontics, kinematics, pediatrics, forensic science, etc. Most studies, however, do not take in...