Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
The ongoing integration of quantum chemistry, statistical mechanics, and artificial intelligence is paving the route toward more effective and accurate strategies for the investigation of the spectroscopic properties of medium-to-large size chromophores in condensed phases. In this context we are developing a novel workflow aimed at improving the generality, reliability, and ease of use of the ava...
BACKGROUND: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (principles and standards), providing access to data for research while protecting patient confidentiality. Accessing sensitive data without compromising the privacy and security of the data is a complex process.
This paper seeks to design, develop, and explore the locomotive dynamics and morphological adaptability of a bacteria-inspired rod-like soft robot pro...
Learning continually from a stream of training data or tasks with an ability to learn the unseen classes using a zero-shot learning framework is gaini...
Instance segmentation has been developing rapidly in recent years. Mask R-CNN, a two-stage instance segmentation approach, has demonstrated exceptiona...
Predicting river runoff accurately is of substantial significance for flood control, water resource allocation, and basin ecological dispatching. To e...
Keeping computers secure is becoming challenging as networks grow and new network-based technologies emerge. Cybercriminals' attack surface expands wi...
With the exploration and development of marine resources, deep learning is more and more widely used in underwater image processing. However, the qual...
Commonly used nested entity recognition methods are span-based entity recognition methods, which focus on learning the head and tail representations o...
The objectives are to solve the problems existing in the current ideological and political theory courses, such as the difficulty of classroom teachin...
The growing availability of scanned whole-slide images (WSIs) has allowed nephropathology to open new possibilities for medical decision-making over h...
Clinically, proper polyp localization in endoscopy images plays a vital role in the follow-up treatment (e.g., surgical planning). Deep convolutional ...
This study considers the boundary stabilization for stochastic delayed Cohen-Grossberg neural networks (SDCGNNs) with diffusion terms by the Lyapunov ...
Manual segmentation of stacks of 2D biomedical images (e.g., histology) is a time-consuming task which can be sped up with semi-automated techniques. ...
In water pipeline systems, monitoring and predicting hydraulic transient events are important to ensure the proper operation of pressure control devic...
In manyclinical settings, a lot of medical image datasets suffer from imbalance problems, which makes predictions of trained models to be biased towar...
The measurement of work time for individual tasks by using video has made a significant contribution to a framework for productivity improvement such ...
Many real-world applications for robots-such as long-term aerial and underwater observation, cross-medium operations, and marine life surveys-require ...
This study was aimed at two image segmentation methods of three-dimensional (3D) U-shaped network (U-Net) and multilevel boundary sensing residual U-s...
Recently, heatmap regression has been widely explored in facial landmark detection and obtained remarkable performance. However, most of the existing ...