AIMC Topic: Infant
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Economic and utilization outcomes of medication management at a large Medicaid plan with disease management pharmacists using a novel artificial intelligence platform from 2018 to 2019: a retrospective observational study using regression methods.
Journal of managed care & specialty pharmacy
May 25, 2021
Medication therapy management (MTM) and comprehensive medication management (CMM) have been practiced by clinical pharmacists as a predominantly manual activity with interventions documented in a record-keeping system. Program evaluations, largely b...
Using deep learning convolutional neural networks to automatically perform cerebral aqueduct CSF flow analysis.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
May 24, 2021
Since the development of phase-contrast magnetic resonance imaging (PC-MRI), quantification of cerebrospinal fluid (CSF) flow across the cerebral aqueduct has been utilized for diagnosis of conditions such as normal pressure hydrocephalus (NPH). This...
Deep-Learning-Driven Quantification of Interstitial Fibrosis in Digitized Kidney Biopsies.
The American journal of pathology
May 23, 2021
Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA ...
Analysing wideband absorbance immittance in normal and ears with otitis media with effusion using machine learning.
Scientific reports
May 20, 2021
Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation of WAI results. This study aimed to develop Machine Learning (ML) too...
Novel AI driven approach to classify infant motor functions.
Scientific reports
May 10, 2021
The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the classic Prechtl general movements assessment (GMA)...
Deep reasoning neural network analysis to predict language deficits from psychometry-driven DWI connectome of young children with persistent language concerns.
Human brain mapping
May 5, 2021
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...
Robot-assisted anorectal pull-through for anorectal malformations with rectourethral and rectovesical fistula: feasibility and short-term outcome.
Surgical endoscopy
Apr 20, 2021
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 and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation.
Journal of medical Internet research
Apr 19, 2021
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.
Automated detection of pneumonia cases using deep transfer learning with paediatric chest X-ray images.
The British journal of radiology
Apr 16, 2021
OBJECTIVE: Pneumonia is a lung infection and causes the inflammation of the small air sacs (Alveoli) in one or both lungs. Proper and faster diagnosis of pneumonia at an early stage is imperative for optimal patient care. Currently, chest X-ray is co...
Model and variable selection using machine learning methods with applications to childhood stunting in Bangladesh.
Informatics for health & social care
Apr 14, 2021
Childhood stunting is a serious public health concern in Bangladesh. Earlier research used conventional statistical methods to identify the risk factors of stunting, and very little is known about the applications and usefulness of machine learning (...
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