Latest AI and machine learning research in work force for healthcare professionals.
Artificial intelligence (AI), the computerized capability of doing tasks, which until recently was thought to be the exclusive domain of human intelligence, has demonstrated great strides in the past decade. The abilities to play games, provide piloting for an automobile, and respond to spoken language are remarkable successes. How are the challenges and opportunities of medicine different from th...
Image generation is a long-standing problem in the machine learning and computer vision areas. In order to generate images with high diversity, we propose a novel model called generative adversarial networks with mixture of t-distributions noise (tGANs). In tGANs, the latent generative space is formulated using a mixture of t-distributions. Particularly, the parameters of the components in the mix...
BACKGROUND: Futurists have predicted that new autonomous technologies, embedded with artificial intelligence (AI) and machine learning (ML), will lead...
UNLABELLED: Constant-force isometric muscle training is useful for increasing the maximal strength , rehabilitation and work-fatigue assessment. Earli...
In the process of rehabilitation training for stroke patients, the rehabilitation effect is positively affected by how much physical activity the pati...
People explosion and fast economic growth are bringing a more serious land resource shortage crisis. Rational land-use allocation can effectively redu...
With the increasing acquisition of large-scale neural recordings comes the challenge of inferring the computations they perform and understanding how ...
Hospitals need to invest a lot of manpower to manually input the contents of medical invoices (nearly 300,000,000 medical invoices a year) into the me...
Classification of the biological activities of chemical substances is important for developing new medicines efficiently. Various machine learning met...
Explaining colour variation among animals at broad geographic scales remains challenging. Here we demonstrate how deep learning-a form of artificial i...
We present a machine learning approach to automated force field development in dissipative particle dynamics (DPD). The approach employs Bayesian opti...
OBJECTIVE: To determine barriers associated with the transition from bedside assistant to console surgeon for general surgery residents in the era of ...
Current histological and anatomical analysis techniques, including fluorescence in situ hybridisation, immunohistochemistry, immunofluorescence, immun...
Real time hand movement trajectory tracking based on machine learning approaches may assist the early identification of dementia in ageing Deaf indivi...
Identifying new indications for existing drugs may reduce costs and expedites drug development. Drug-related disease predictions typically combined he...
Sustainable urban development (SUD) requires a balance between economic growth, social well-being, and environmental protection. Oftentimes, urban pol...
Artificial neural networks, trained to perform cognitive tasks, have recently been used as models for neural recordings from animals performing these ...
Sensor-based human activity recognition (HAR) has attracted interest both in academic and applied fields, and can be utilized in health-related areas,...
The rehabilitation robot is an application of robotic technology for people with limb disabilities. This paper investigates a new applicable and effec...
BACKGROUND AND OBJECTIVE: The shortage of ophthalmologists in rural areas in China causes a lot of cataract patients not getting timely diagnosis and ...