AIMC Topic: Middle Aged

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Cerebral microbleed detection using Susceptibility Weighted Imaging and deep learning.

NeuroImage
Detecting cerebral microbleeds (CMBs) is important in diagnosing a variety of diseases including dementia, stroke and traumatic brain injury. However, manual detection of CMBs can be time-consuming and prone to errors, whereas the current automatic a...

Effect of repetitive transcranial magnetic stimulation combined with robot-assisted training on wrist muscle activation post-stroke.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To compare the effects of active assisted wrist extension training, using a robotic exoskeleton (RW), with simultaneous 5 Hz (rTMS + RW) or Sham rTMS (Sham rTMS + RW) over the ipsilesional extensor carpi radialis motor cortical representat...

Dry eye is matched by increased intrasubject variability in tear osmolarity as confirmed by machine learning approach.

Archivos de la Sociedad Espanola de Oftalmologia
OBJECTIVE: Because of high variability, tear film osmolarity measures have been questioned in dry eye assessment. Understanding the origin of such variability would aid data interpretation. This study aims to evaluate osmolarity variability in a clin...

Prediction of antiepileptic drug treatment outcomes of patients with newly diagnosed epilepsy by machine learning.

Epilepsy & behavior : E&B
OBJECTIVE: The objective of this study was to build a supervised machine learning-based classifier, which can accurately predict the outcomes of antiepileptic drug (AED) treatment of patients with newly diagnosed epilepsy.

Model-free prostate cancer segmentation from dynamic contrast-enhanced MRI with recurrent convolutional networks: A feasibility study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is a method of temporal imaging that is commonly used to aid in prostate cancer (PCa) diagnosis and staging. Typically, machine learning models designed for the segmentation and detecti...

Effects of Assistive Robot Behavior on Impressions of Patient Psychological Attributes: Vignette-Based Human-Robot Interaction Study.

Journal of medical Internet research
BACKGROUND: As robots are increasingly designed for health management applications, it is critical to not only consider the effects robots will have on patients but also consider a patient's wider social network, including the patient's caregivers an...

Machine learning in the clinical and language characterisation of primary progressive aphasia variants.

Cortex; a journal devoted to the study of the nervous system and behavior
INTRODUCTION: Primary progressive aphasia (PPA) is a clinical syndrome of neurodegenerative origin with 3 main variants: non-fluent, semantic, and logopenic. However, there is some controversy about the existence of additional subtypes. Our aim was t...

Detection of respiratory rate using a classifier of waves in the signal from a FBG-based vital signs sensor.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Monitoring of changes in respiratory rate provides information on a patient's psychophysical state. This paper presents a respiratory rate detection method based on analysis of signals from a fiber Bragg grating (FBG)-based ...

Towards more Accessible Precision Medicine: Building a more Transferable Machine Learning Model to Support Prognostic Decisions for Micro- and Macrovascular Complications of Type 2 Diabetes Mellitus.

Journal of medical systems
Although machine learning models are increasingly being developed for clinical decision support for patients with type 2 diabetes, the adoption of these models into clinical practice remains limited. Currently, machine learning (ML) models are being ...