Latest AI and machine learning research in work force for healthcare professionals.
Bio-signal based assessment for upper-limb functions is an attractive technology for rehabilitation. In this work, an upper-limb function evaluator is developed based on biological signals, which could be used for selecting different robotic training protocols. Interaction force (IF) and participation level (PL, processed surface electromyography (sEMG) signals) are used as the key bio-signal inpu...
Life expectancy is rising in most parts of the world as is the prevalence of chronic diseases. Suboptimal adherence to long-term medications is still rather the norm than the exception, although it is well known that suboptimal adherence compromises the therapeutic effectiveness. Information and communications technology provides new concepts for improving adherence to medications. These so-called...
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working ...
Recent years have witnessed the success of deep learning methods in human activity recognition (HAR). The longstanding shortage of labeled activity da...
According to diagnostic criteria, skin tumors can be divided into three categories: benign, low degree and high degree malignancy. For high degree mal...
Robotics teleoperation enables human operators to control the movements of distally located robots. The development of new wearable interfaces as alte...
OBJECTIVES: This paper provides a discussion about the potential scope of applicability of Artificial Intelligence methods within the telehealth domai...
BACKGROUND AND OBJECTIVES: With rapid development of telehealth system and cloud platform, traditional 12-ECG signals with high resolution generate he...
The feasibility of integrating remote presence technology within a simulation scenario for psychiatric-mental health nursing (PMHN) students to develo...
BACKGROUND: With global aging, robots are considered a promising solution for handling the shortage of aged care and companionships. However, these te...
The classification of medical images is an essential task in computer-aided diagnosis, medical image retrieval and mining. Although deep learning has ...
The structure and performance of neural networks are intimately connected, and by use of evolutionary algorithms, neural network structures optimally ...
Automatic diagnosing lung cancer from computed tomography scans involves two steps: detect all suspicious lesions (pulmonary nodules) and evaluate the...
Artificial intelligence (AI)-based methods have emerged as powerful tools to transform medical care. Although machine learning classifiers (MLCs) have...
Artificial intelligence (AI) involves computational networks (neural networks) that simulate human intelligence. The incorporation of AI in radiology ...
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including pr...
Musculoskeletal models permit the determination of internal forces acting during dynamic movement, which is clinically useful, but traditional methods...
Skeletal muscle forces may be estimated using rigid musculoskeletal models and neural networks. Neural network (NN) approach has the advantages of rea...
Robot-assisted bilateral training is being developed as a new rehabilitation approach for stroke patients. However, there is still a lack of understan...
INTRODUCTION: Currently, the shortage of organs available for kidney transplantation and a change in donors' and recipients' profiles (elderly, with c...