AIMC Topic: Humans

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Olfactory Testing in Parkinson Disease and REM Behavior Disorder: A Machine Learning Approach.

Neurology
OBJECTIVE: We sought to identify an abbreviated test of impaired olfaction amenable for use in busy clinical environments in prodromal (isolated REM sleep behavior disorder [iRBD]) and manifest Parkinson disease (PD).

Leveraging electronic health records data to predict multiple sclerosis disease activity.

Annals of clinical and translational neurology
OBJECTIVE: No relapse risk prediction tool is currently available to guide treatment selection for multiple sclerosis (MS). Leveraging electronic health record (EHR) data readily available at the point of care, we developed a clinical tool for predic...

Low-dose CT urography using deep learning image reconstruction: a prospective study for comparison with conventional CT urography.

The British journal of radiology
OBJECTIVES: To compare the image quality of low-dose CT urography (LD-CTU) using deep learning image reconstruction (DLIR) with conventional CTU (C-CTU) using adaptive statistical iterative reconstruction (ASIR-V).

Validation of a deep-learning semantic segmentation approach to fully automate MRI-based left-ventricular deformation analysis in cardiotoxicity.

The British journal of radiology
OBJECTIVE: Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to chemotherapy for breast cancer. This study investigated an ...

A deep learning-based system for bile duct annotation and station recognition in linear endoscopic ultrasound.

EBioMedicine
BACKGROUND: Detailed evaluation of bile duct (BD) is main focus during endoscopic ultrasound (EUS). The aim of this study was to develop a system for EUS BD scanning augmentation.

Intraoral radiograph anatomical region classification using neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Dental radiography represents 13% of all radiological diagnostic imaging. Eliminating the need for manual classification of digital intraoral radiographs could be especially impactful in terms of time savings and metadata quality. However, a...