AIMC Topic: Infant, Newborn

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Automatically determining cause of death from verbal autopsy narratives.

BMC medical informatics and decision making
BACKGROUND: A verbal autopsy (VA) is a post-hoc written interview report of the symptoms preceding a person's death in cases where no official cause of death (CoD) was determined by a physician. Current leading automated VA coding methods primarily u...

Automated Ventricular System Segmentation in Paediatric Patients Treated for Hydrocephalus Using Deep Learning Methods.

BioMed research international
Hydrocephalus is a common neurological condition that can have traumatic ramifications and can be lethal without treatment. Nowadays, during therapy radiologists have to spend a vast amount of time assessing the volume of cerebrospinal fluid (CSF) by...

Object Detection During Newborn Resuscitation Activities.

IEEE journal of biomedical and health informatics
OBJECTIVE: Birth asphyxia is a major newborn mortality problem in low-resource countries. International guideline provides treatment recommendations; however, the importance and effect of the different treatments are not fully explored. The available...

A machine learning investigation of volumetric and functional MRI abnormalities in adults born preterm.

Human brain mapping
Imaging studies have characterized functional and structural brain abnormalities in adults after premature birth, but these investigations have mostly used univariate methods that do not account for hypothesized interdependencies between brain region...

Role of deep learning in infant brain MRI analysis.

Magnetic resonance imaging
Deep learning algorithms and in particular convolutional networks have shown tremendous success in medical image analysis applications, though relatively few methods have been applied to infant MRI data due numerous inherent challenges such as inhomo...

Task-Oriented Feature-Fused Network With Multivariate Dataset for Joint Face Analysis.

IEEE transactions on cybernetics
Deep multitask learning for face analysis has received increasing attentions. From literature, most existing methods focus on optimizing a main task by jointly learning several auxiliary tasks. It is challenging to consider the performance of each ta...

Predicting Inpatient Payments Prior to Lower Extremity Arthroplasty Using Deep Learning: Which Model Architecture Is Best?

The Journal of arthroplasty
BACKGROUND: Recent advances in machine learning have given rise to deep learning, which uses hierarchical layers to build models, offering the ability to advance value-based healthcare by better predicting patient outcomes and costs of a given treatm...

Statistical supervised meta-ensemble algorithm for medical record linkage.

Journal of biomedical informatics
Identifying unique patients across multiple care facilities or services is a major challenge in providing continuous care and undertaking health research. Identifying and linking patients without compromising privacy and security is an emerging issue...

Towards the automated economic assessment of newborn screening for rare diseases.

Journal of biomedical informatics
OBJECTIVE: Economic assessments of newborn screening programs for rare diseases involve the use of models and require huge efforts to synthesize information from different sources. Sharing and automatically or semi-automatically reusing this informat...