AI Medical Compendium Topic:
Infant

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Deep-Learning-Based Detection of Infants with Autism Spectrum Disorder Using Auto-Encoder Feature Representation.

Sensors (Basel, Switzerland)
Autism spectrum disorder (ASD) is a developmental disorder with a life-span disability. While diagnostic instruments have been developed and qualified based on the accuracy of the discrimination of children with ASD from typical development (TD) chil...

Performance evaluation of machine learning-based infectious screening flags on the HORIBA Medical Yumizen H550 Haematology Analyzer for vivax malaria and dengue fever.

Malaria journal
BACKGROUND: Automated detection of malaria and dengue infection has been actively researched for more than two decades. Although many improvements have been achieved, these solutions remain too expensive for most laboratories and clinics in developin...

Automatic eye localization for hospitalized infants and children using convolutional neural networks.

International journal of medical informatics
BACKGROUND: Reliable localization and tracking of the eye region in the pediatric hospital environment is a significant challenge for clinical decision support and patient monitoring applications. Existing work in eye localization achieves high perfo...

Development and utility assessment of a machine learning bloodstream infection classifier in pediatric patients receiving cancer treatments.

BMC cancer
BACKGROUND: Objectives were to build a machine learning algorithm to identify bloodstream infection (BSI) among pediatric patients with cancer and hematopoietic stem cell transplantation (HSCT) recipients, and to compare this approach with presence o...

Prediction of Cranial Radiotherapy Treatment in Pediatric Acute Lymphoblastic Leukemia Patients Using Machine Learning: A Case Study at MAHAK Hospital.

Asian Pacific journal of cancer prevention : APJCP
BACKGROUND: Acute Lymphoblastic Leukemia (ALL) is the most common blood disease in children and is responsible for the most deaths amongst children. Due to major improvements in the treatment protocols in the 50-years period, the survivability of thi...

Machine learning model demonstrates stunting at birth and systemic inflammatory biomarkers as predictors of subsequent infant growth - a four-year prospective study.

BMC pediatrics
BACKGROUND: Stunting affects up to one-third of the children in low-to-middle income countries (LMICs) and has been correlated with decline in cognitive capacity and vaccine immunogenicity. Early identification of infants at risk is critical for earl...

Traditional and New Methods of Bone Age Assessment-An Overview.

Journal of clinical research in pediatric endocrinology
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...

Fast body part segmentation and tracking of neonatal video data using deep learning.

Medical & biological engineering & computing
Photoplethysmography imaging (PPGI) for non-contact monitoring of preterm infants in the neonatal intensive care unit (NICU) is a promising technology, as it could reduce medical adhesive-related skin injuries and associated complications. For practi...

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...