Artificial Intelligence Trust, risk and security management (AI trism): Frameworks, applications, challenges and future research directions
Artificial Intelligence (AI) has become pervasive, enabling transformative advancements in
various industries including smart city, smart healthcare, smart manufacturing, smart virtual …
various industries including smart city, smart healthcare, smart manufacturing, smart virtual …
Multimodal data fusion for cancer biomarker discovery with deep learning
Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …
On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Iti-gen: Inclusive text-to-image generation
Text-to-image generative models often reflect the biases of the training data, leading to
unequal representations of underrepresented groups. This study investigates inclusive text …
unequal representations of underrepresented groups. This study investigates inclusive text …
Opening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generators
Large language models that exhibit instruction-following behaviour represent one of the
biggest recent upheavals in conversational interfaces, a trend in large part fuelled by the …
biggest recent upheavals in conversational interfaces, a trend in large part fuelled by the …
A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring
The complex relationships between continuously monitored health signals and therapeutic
regimens can be modelled via machine learning. However, the clinical implementation of …
regimens can be modelled via machine learning. However, the clinical implementation of …
Converting nanotoxicity data to information using artificial intelligence and simulation
Decades of nanotoxicology research have generated extensive and diverse data sets.
However, data is not equal to information. The question is how to extract critical information …
However, data is not equal to information. The question is how to extract critical information …
[HTML][HTML] A review of uncertainty estimation and its application in medical imaging
The use of AI systems in healthcare for the early screening of diseases is of great clinical
importance. Deep learning has shown great promise in medical imaging, but the reliability …
importance. Deep learning has shown great promise in medical imaging, but the reliability …
Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements
Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
Threats to terrestrial plants from emerging nanoplastics
Nanoplastics are ubiquitous in ecosystems and impact planetary health. However, our
current understanding on the impacts of nanoplastics upon terrestrial plants is fragmented …
current understanding on the impacts of nanoplastics upon terrestrial plants is fragmented …