AIMC Topic: Adolescent

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Natural Language Processing-Identified Problem Opioid Use and Its Associated Health Care Costs.

Journal of pain & palliative care pharmacotherapy
Use of prescription opioids and problems of abuse and addiction have increased over the past decade. Claims-based studies have documented substantial economic burden of opioid abuse. This study utilized electronic health record (EHR) data to identify...

Prediction of mortality following pediatric heart transplant using machine learning algorithms.

Pediatric transplantation
BACKGROUND: Optimizing transplant candidates' priority for donor organs depends on the accurate assessment of post-transplant outcomes. Due to the complexity of transplantation and the wide range of possible serious complications, recipient outcomes ...

Robot-assisted Tongue Base Resection ensures favorable therapeutic outcome to Obstructive Sleep Apnea patients with Lingual tonsil hypertrophy.

Scientific reports
Tongue base (TB) narrowing is recognized as a significant site of upper airway collapse during sleep in obstructive sleep apnea (OSA) patients and robot technology is expected to have promising clinical utility in OSA patients with TB narrowing. The ...

Physical characteristics not psychological state or trait characteristics predict motion during resting state fMRI.

Scientific reports
Head motion (HM) during fMRI acquisition can significantly affect measures of brain activity or connectivity even after correction with preprocessing methods. Moreover, any systematic relationship between HM and variables of interest can introduce sy...

Robotic hand illusion with tactile feedback: Unravelling the relative contribution of visuotactile and visuomotor input to the representation of body parts in space.

PloS one
The rubber hand illusion describes a phenomenon in which participants experience a rubber hand as being part of their body by the synchronous application of visuotactile stimulation to the real and the artificial limb. In the recently introduced robo...

Intervening Nidal Brain Parenchyma and Risk of Radiation-Induced Changes After Radiosurgery for Brain Arteriovenous Malformation: A Study Using an Unsupervised Machine Learning Algorithm.

World neurosurgery
OBJECTIVE: To assess the sensitivity and specificity of arteriovenous malformation (AVM) nidal component identification and quantification using an unsupervised machine learning algorithm and to evaluate the association between intervening nidal brai...

Seizure detection by convolutional neural network-based analysis of scalp electroencephalography plot images.

NeuroImage. Clinical
We hypothesized that expert epileptologists can detect seizures directly by visually analyzing EEG plot images, unlike automated methods that analyze spectro-temporal features or complex, non-stationary features of EEG signals. If so, seizure detecti...

Dermoscopy diagnosis of cancerous lesions utilizing dual deep learning algorithms via visual and audio (sonification) outputs: Laboratory and prospective observational studies.

EBioMedicine
BACKGROUND: Early diagnosis of skin cancer lesions by dermoscopy, the gold standard in dermatological imaging, calls for a diagnostic upscale. The aim of the study was to improve the accuracy of dermoscopic skin cancer diagnosis through use of novel ...

Breast mass classification in sonography with transfer learning using a deep convolutional neural network and color conversion.

Medical physics
PURPOSE: We propose a deep learning-based approach to breast mass classification in sonography and compare it with the assessment of four experienced radiologists employing breast imaging reporting and data system 4th edition lexicon and assessment p...

Predicting Hemodynamic Shock from Thermal Images using Machine Learning.

Scientific reports
Proactive detection of hemodynamic shock can prevent organ failure and save lives. Thermal imaging is a non-invasive, non-contact modality to capture body surface temperature with the potential to reveal underlying perfusion disturbance in shock. In ...