AIMC Topic: Female

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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...

Atrial fibrillation classification based on convolutional neural networks.

BMC medical informatics and decision making
BACKGROUND: The global age-adjusted mortality rate related to atrial fibrillation (AF) registered a rapid growth in the last four decades, i.e., from 0.8 to 1.6 and 0.9 to 1.7 per 100,000 for men and women during 1990-2010, respectively. In this cont...

A Virtual Counseling Application Using Artificial Intelligence for Communication Skills Training in Nursing Education: Development Study.

Journal of medical Internet research
BACKGROUND: The ability of nursing undergraduates to communicate effectively with health care providers, patients, and their family members is crucial to their nursing professions as these can affect patient outcomes. However, the traditional use of ...

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...

A hierarchical sequential neural network with feature fusion for sleep staging based on EOG and RR signals.

Journal of neural engineering
OBJECTIVE: Currently, the automatic sleep staging methods mainly face two problems: the first problem is that although the algorithms which use electroencephalogram (EEG) signals perform well, acquiring EEG signals is complicated and uncomfortable; 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...

The hidden information in patient-reported outcomes and clinician-assessed outcomes: multiple sclerosis as a proof of concept of a machine learning approach.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Machine learning (ML) applied to patient-reported (PROs) and clinical-assessed outcomes (CAOs) could favour a more predictive and personalized medicine. Our aim was to confirm the important role of applying ML to PROs and CAOs of people with relapsin...

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 ...

A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis.

Journal of sports sciences
The purpose of this study was to develop an automated method for identifying and classifying change of direction (COD) movements in professional tennis using tracking data. Three sport science and strength and conditioning experts coded match-play fo...

Myoelectric Control of a Soft Hand Exoskeleton Using Kinematic Synergies.

IEEE transactions on biomedical circuits and systems
Soft hand exoskeletons offer a lightweight, low-profile alternative to rigid rehabilitative robotic systems, enabling their use to restore activities of daily living (ADL) in those with hand paresis due to stroke or other conditions. The hand exoskel...