Medical Ethics / Professional Responsibility

MRBENet: A Multiresolution Boundary Enhancement Network for Salient Object Detection.

Salient Object Detection (SOD) simulates the human visual perception in locating the most attractive objects in the images. Existing methods based on convolutional neural networks have proven to be highly effective for SOD. However, in some cases, these methods cannot satisfy the need of both accurately detecting intact objects and maintaining their boundary details. In this paper, we present a Mu...

Deep Learning for Encrypted Traffic Classification and Unknown Data Detection.

Despite the widespread use of encryption techniques to provide confidentiality over Internet communications, mobile device users are still susceptible to privacy and security risks. In this paper, a novel Deep Neural Network (DNN) based on a user activity detection framework is proposed to identify fine-grained user activities performed on mobile applications (known as in-app activities) from a sn...

De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models.

Electronic Medical Records (EMRs) contain clinical narrative text that is of great potential value to medical researchers. However, this information i...

FBCU-Net: A fine-grained context modeling network using boundary semantic features for medical image segmentation.

The performance of deep learning-based medical image segmentation methods largely depends on the segmentation accuracy of tissue boundaries. However, ...

Integration of Quantum Chemistry, Statistical Mechanics, and Artificial Intelligence for Computational Spectroscopy: The UV-Vis Spectrum of TEMPO Radical in Different Solvents.

The ongoing integration of quantum chemistry, statistical mechanics, and artificial intelligence is paving the route toward more effective and accurat...

Next-Generation Capabilities in Trusted Research Environments: Interview Study.

BACKGROUND: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (princi...

Bacteria-inspired magnetically actuated rod-like soft robot in viscous fluids.

This paper seeks to design, develop, and explore the locomotive dynamics and morphological adaptability of a bacteria-inspired rod-like soft robot pro...

Tf-GCZSL: Task-free generalized continual zero-shot learning.

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...

BRefine: Achieving High-Quality Instance Segmentation.

Instance segmentation has been developing rapidly in recent years. Mask R-CNN, a two-stage instance segmentation approach, has demonstrated exceptiona...

Stepwise decomposition-integration-prediction framework for runoff forecasting considering boundary correction.

Predicting river runoff accurately is of substantial significance for flood control, water resource allocation, and basin ecological dispatching. To e...

Apache Spark and Deep Learning Models for High-Performance Network Intrusion Detection Using CSE-CIC-IDS2018.

Keeping computers secure is becoming challenging as networks grow and new network-based technologies emerge. Cybercriminals' attack surface expands wi...

Semantic segmentation method of underwater images based on encoder-decoder architecture.

With the exploration and development of marine resources, deep learning is more and more widely used in underwater image processing. However, the qual...

Research on Named Entity Recognition Based on Multi-Task Learning and Biaffine Mechanism.

Commonly used nested entity recognition methods are span-based entity recognition methods, which focus on learning the head and tail representations o...

Analysis of the Current Situation of Teaching and Learning of Ideological and Political Theory Courses by Deep Learning.

The objectives are to solve the problems existing in the current ideological and political theory courses, such as the difficulty of classroom teachin...

Boundary-aware glomerulus segmentation: Toward one-to-many stain generalization.

The growing availability of scanned whole-slide images (WSIs) has allowed nephropathology to open new possibilities for medical decision-making over h...

Boundary Constraint Network With Cross Layer Feature Integration for Polyp Segmentation.

Clinically, proper polyp localization in endoscopy images plays a vital role in the follow-up treatment (e.g., surgical planning). Deep convolutional ...

Boundary Stabilization of Stochastic Delayed Cohen-Grossberg Neural Networks With Diffusion Terms.

This study considers the boundary stabilization for stochastic delayed Cohen-Grossberg neural networks (SDCGNNs) with diffusion terms by the Lyapunov ...

Deep active learning for suggestive segmentation of biomedical image stacks via optimisation of Dice scores and traced boundary length.

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. ...

Physics-informed neural networks for hydraulic transient analysis in pipeline systems.

In water pipeline systems, monitoring and predicting hydraulic transient events are important to ensure the proper operation of pressure control devic...

Handling Imbalanced Data: Uncertainty-Guided Virtual Adversarial Training With Batch Nuclear-Norm Optimization for Semi-Supervised Medical Image Classification.

In manyclinical settings, a lot of medical image datasets suffer from imbalance problems, which makes predictions of trained models to be biased towar...