AIMC Topic: Humans

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Machine Learning in Neuroimaging: A New Approach to Understand Acupuncture for Neuroplasticity.

Neural plasticity
The effects of acupuncture facilitating neural plasticity for treating diseases have been identified by clinical and experimental studies. In the last two decades, the application of neuroimaging techniques in acupuncture research provided visualized...

Importance of anthropometric features to predict physical performance in elite youth soccer: a machine learning approach.

Research in sports medicine (Print)
The present study aimed to determine the contribution of soccer players' anthropometric features to predict their physical performance. Sixteen players, from a professional youth soccer academy, were recruited. Several anthropometric features such as...

An ensemble of deep neural networks for kidney ultrasound image classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Chronic kidney disease is a worldwide health issue which includes not only kidney failure but also complications of reduced kidney functionality. Cyst formation, nephrolithiasis or kidney stone, and renal cell carcinoma or k...

Linear predictive coding distinguishes spectral EEG features of Parkinson's disease.

Parkinsonism & related disorders
OBJECTIVE: We have developed and validated a novel EEG-based signal processing approach to distinguish PD and control patients: Linear-predictive-coding EEG Algorithm for PD (LEAPD). This method efficiently encodes EEG time series into features that ...

Deep Learning-Based Real-Time Multiple-Person Action Recognition System.

Sensors (Basel, Switzerland)
Action recognition has gained great attention in automatic video analysis, greatly reducing the cost of human resources for smart surveillance. Most methods, however, focus on the detection of only one action event for a single person in a well-segme...

WiGAN: A WiFi Based Gesture Recognition System with GANs.

Sensors (Basel, Switzerland)
In recent years, a series of research experiments have been conducted on WiFi-based gesture recognition. However, current recognition systems are still facing the challenge of small samples and environmental dependence. To deal with the problem of pe...

Gait Activity Classification on Unbalanced Data from Inertial Sensors Using Shallow and Deep Learning.

Sensors (Basel, Switzerland)
Activity recognition is one of the most active areas of research in ubiquitous computing. In particular, gait activity recognition is useful to identify various risk factors in people's health that are directly related to their physical activity. One...

A novel image signature-based radiomics method to achieve precise diagnosis and prognostic stratification of gliomas.

Laboratory investigation; a journal of technical methods and pathology
Radiomics has potential advantages in the noninvasive histopathological and molecular diagnosis of gliomas. We aimed to develop a novel image signature (IS)-based radiomics model to achieve multilayered preoperative diagnosis and prognostic stratific...

Spectral-Spatial Features Integrated Convolution Neural Network for Breast Cancer Classification.

Sensors (Basel, Switzerland)
Cancer identification and classification from histopathological images of the breast depends greatly on experts, and computer-aided diagnosis can play an important role in disagreement of experts. This automatic process has increased the accuracy of ...