Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
Semi-supervised domain adaptation (SSDA) is quite a challenging problem requiring methods to overcom...
We propose an adaptive neural-network-based fault-tolerant control scheme for a flexible string cons...
As an important part of video understanding, temporal action detection (TAD) has wide application sc...
Automated segmentation of medical images is crucial for disease diagnosis and treatment planning. Me...
Federated learning (FL) is a computational paradigm that enables organizations to collaborate on mac...
The existence of various sounds from different natural and unnatural sources in the deep sea has cau...
A revolution in network technology has been ushered in by software defined networking (SDN), which m...
Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which can lead t...
A probabilistic neural network has been implemented to predict the malignancy of breast cancer cells...
The scarcity of high-quality annotations in many application scenarios has recently led to an increa...
Salient Object Detection (SOD) simulates the human visual perception in locating the most attractive...
Despite the widespread use of encryption techniques to provide confidentiality over Internet communi...
The performance of deep learning-based medical image segmentation methods largely depends on the seg...
Electronic Medical Records (EMRs) contain clinical narrative text that is of great potential value t...
The ongoing integration of quantum chemistry, statistical mechanics, and artificial intelligence is ...
BACKGROUND: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment suppo...
OBJECTIVE: With the rapid growth of high-speed deep-tissue imaging in biomedical research, there is ...
This paper seeks to design, develop, and explore the locomotive dynamics and morphological adaptabil...
In recent years, machine learning (ML) models have been found to quickly predict various molecular p...
Learning continually from a stream of training data or tasks with an ability to learn the unseen cla...
Instance segmentation has been developing rapidly in recent years. Mask R-CNN, a two-stage instance ...