AIMC Topic: Aged

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Hash Transformation and Machine Learning-Based Decision-Making Classifier Improved the Accuracy Rate of Automated Parkinson's Disease Screening.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Digitalized hand-drawn pattern is a noninvasive and reproducible assistive manner to obtain hand actions and motions for evaluating functional tremors and upper-limb movement disorders. In this study, spirals and straight lines in polar coordinates a...

Computational modeling of the effects of EEG volume conduction on functional connectivity metrics. Application to Alzheimer's disease continuum.

Journal of neural engineering
OBJECTIVE: The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume conduction in different measures of functional connectivity and to characterize the EEG coupling alterations at the different stages of dementia due t...

True single-port cholecystectomy with ICG cholangiography through a single 15-mm trocar using the new surgical platform "symphonX": first human case study with a commercially available device.

Surgical endoscopy
BACKGROUND: Minimally invasive single-port surgery is often associated with large incisions up to 2-3 cm, complicated handling due to the lack of triangulation, and instrument crossing. Aim of this prospective study was to perform true single-port su...

Can We Improve Prediction of Adverse Surgical Outcomes? Development of a Surgical Complexity Score Using a Novel Machine Learning Technique.

Journal of the American College of Surgeons
BACKGROUND: An optimal method to quantify surgical complexity using patient comorbidities derived from administrative billing data is lacking. We sought to develop a novel, easy-to-use surgical Complexity Score to accurately predict adverse outcomes ...

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images.

European radiology experimental
BACKGROUND: Liver alignment between series/exams is challenged by dynamic morphology or variability in patient positioning or motion. Image registration can improve image interpretation and lesion co-localization. We assessed the performance of a con...

Integrated robotics platform with haptic control differentiates subjects with Parkinson's disease from controls and quantifies the motor effects of levodopa.

Journal of neuroengineering and rehabilitation
BACKGROUND: The use of integrated robotic technology to quantify the spectrum of motor symptoms of Parkinson's Disease (PD) has the potential to facilitate objective assessment that is independent of clinical ratings. The purpose of this study is to ...

Factor Xa inhibitors in clinical practice: Comparison of pharmacokinetic profiles.

Drug metabolism and pharmacokinetics
BACKGROUND: The anticoagulant actions of oral direct factor Xa (FXa) inhibitors can be inferred from their observed plasma concentrations; however, the steady-state pharmacokinetics (PK) of different FXa inhibitors have not been compared in clinicall...

A machine learning approach for the prediction of pulmonary hypertension.

PloS one
BACKGROUND: Machine learning (ML) is a powerful tool for identifying and structuring several informative variables for predictive tasks. Here, we investigated how ML algorithms may assist in echocardiographic pulmonary hypertension (PH) prediction, w...

Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
INTRODUCTION: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects. The automatic contouring algorithms th...