Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predict the outcomes following methadone poisoning. This six-year retrospective longitudinal study utiliz...
Journal of magnetic resonance imaging : JMRI
Nov 9, 2023
BACKGROUND: The T2* value of interventricular septum is routinely reported for grading myocardial iron load in thalassemia major, and automatic segmentation of septum could shorten analysis time and reduce interobserver variability.
For patients with testicular tumors who need the surgical management, open retroperitoneal lymph node dissection (O-RPLND) is considered the gold standard treatment. However, recently, robot-assisted RPLND (R-RPLND) has gained popularity as a minimal...
: Orthodontics is a field that has seen significant advancements in recent years, with technology playing a crucial role in improving diagnosis and treatment planning. The study aimed to implement artificial intelligence to predict the arch width as ...
OBJECTIVE: To systematically compare and rank the accuracy of AI-based intraocular lens (IOL) power calculation formulas and traditional IOL formulas in highly myopic eyes.
Monitoring and quantifying movement behavior is crucial for improving the health of individuals with cerebral palsy (CP). We have modeled and trained an image-based Convolutional Neural Network (CNN) to recognize specific movement classifiers relevan...
CONTEXT/OBJECTIVE: To explore changes in gait functions for patients with chronic spinal cord injury (SCI) before and after standard rehabilitation and rehabilitation with a wearable hip device, explore the utility of robot-assisted gait training (RA...
Journal of magnetic resonance imaging : JMRI
Nov 7, 2023
BACKGROUND: Breast MRI has been recommended as supplemental screening tool to mammography and breast ultrasound of breast cancer by international guidelines, but its long examination time and use of contrast material remains concerning.
Aging is an important risk factor for disease, leading to morphological change that can be assessed on Computed Tomography (CT) scans. We propose a deep learning model for automated age estimation based on CT- scans of the thorax and abdomen generate...
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