Anemia

Research on exercise fatigue estimation method of Pilates rehabilitation based on ECG and sEMG feature fusion.

PURPOSE: Surface electromyography (sEMG) is vulnerable to environmental interference, low recognition rate and poor stability. Electrocardiogram (ECG) signals with rich information were introduced into sEMG to improve the recognition rate of fatigue assessment in the process of rehabilitation.

Motion Fatigue State Detection Based on Neural Networks.

Aiming at the problem of fatigue state detection at the back of sports, a cascade deep learning detection system structure is designed, and a convolutional neural network fatigue state detection model based on multiscale pooling is proposed. Firstly, face detection is carried out by a deep learning model MTCNN to extract eye and mouth regions. Aiming at the problem of eye and mouth state represent...

Profiling of 35 Cases of Hb S/Hb E (: c.20A>T/: c.79G>a), Disease and Association with α-Thalassemia and β-Globin Gene Cluster Haplotypes from Odisha, India.

Hb S/Hb E (: c.20A>T/: c.79G>A) is an uncommon variant of sickle cell disease resulting from coinheritance of Hb S and Hb E. Clinico-hematological and...

Human-robot-robot cooperative control using positioning robot and 1-DOF traction device for robot-assisted fracture reduction system.

While performing musculoskeletal long bone fracture reduction surgery, assistant surgeons can often suffer from physical fatigue as they provide resis...

Anti-Fatigue and Exercise Performance Improvement Effect of Extract in Mice.

(GT) is a native perennial plant growing across the coastline areas in Taiwan. The current study aimed to examine the efficacy of GT extract in ameli...

Towards functional robotic training: motor learning of dynamic tasks is enhanced by haptic rendering but hampered by arm weight support.

BACKGROUND: Current robot-aided training allows for high-intensity training but might hamper the transfer of learned skills to real daily tasks. Many ...

Deep learning for gastroscopic images: computer-aided techniques for clinicians.

Gastric disease is a major health problem worldwide. Gastroscopy is the main method and the gold standard used to screen and diagnose many gastric dis...

A New Approach of Fatigue Classification Based on Data of Tongue and Pulse With Machine Learning.

BACKGROUND: Fatigue is a common and subjective symptom, which is associated with many diseases and suboptimal health status. A reliable and evidence-b...

Establishment and External Validation of a Hypoxia-Derived Gene Signature for Robustly Predicting Prognosis and Therapeutic Responses in Glioblastoma Multiforme.

OBJECTIVE: Hypoxia presents a salient feature investigated in most solid tumors that holds key roles in cancer progression, including glioblastoma mul...

Identification of parameters and formulation of a statistical and machine learning model to identify Babesia canis infections in dogs using available ADVIA hematology analyzer data.

BACKGROUND: Canine babesiosis is an important tick-borne disease in endemic regions. One of the relevant subspecies in Europe is Babesia canis, and it...

Artificial Intelligence for Classifying and Archiving Orthodontic Images.

One of the main requirements for orthodontic treatment is continuous image acquisition. However, the conventional system of orthodontic image acquisit...

Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients.

Acute coronary syndromes (ACS) are a leading cause of deaths worldwide, yet the diagnosis and treatment of this group of diseases represent a signific...

Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model.

This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep learning model to make the technique non-invasive c...

Application of Deep Learning in Lung Cancer Imaging Diagnosis.

Lung cancer is one of the malignant tumors with the highest fatality rate and nearest to our lives. It poses a great threat to human health and it mai...

Fatigue Crack Evaluation with the Guided Wave-Convolutional Neural Network Ensemble and Differential Wavelet Spectrogram.

On-line fatigue crack evaluation is crucial for ensuring the structural safety and reducing the maintenance costs of safety-critical systems. Among st...

Deep Learning in the Classification of Stage of Liver Fibrosis in Chronic Hepatitis B with Magnetic Resonance ADC Images.

Liver fibrosis in chronic hepatitis B is the pathological repair response of the liver to chronic injury, which is a key step in the development of va...

A Memristive Circuit Implementation of Eyes State Detection in Fatigue Driving Based on Biological Long Short-Term Memory Rule.

Biological long short-term memory (B-LSTM) can effectively help human process all kinds of received information. In this work, a memristive B-LSTM cir...

Real-Time Arrhythmia Detection Using Hybrid Convolutional Neural Networks.

Background Accurate detection of arrhythmic events in the intensive care units (ICU) is of paramount significance in providing timely care. However, t...

Evaluation of the Association of Transferrin Receptor Type 2 Gene Mutation (Y250X) with Iron Overload in Major β- Thalassemia.

Thalassemia is an inherited blood disorder in which the body produces defective hemoglobin. One of the important processes to reduce the complication ...

LEDPatNet19: Automated Emotion Recognition Model based on Nonlinear LED Pattern Feature Extraction Function using EEG Signals.

Electroencephalography (EEG) signals collected from human brains have generally been used to diagnose diseases. Moreover, EEG signals can be used in s...