AIMC Topic: Learning

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An equitable and sustainable community of practice framework to address the use of artificial intelligence for global health workforce training.

Human resources for health
Artificial Intelligence (AI) technologies and data science models may hold potential for enabling an understanding of global health inequities and support decision-making related toward possible interventions. However, AI inputs should not perpetuate...

Canonical circuit computations for computer vision.

Biological cybernetics
Advanced computer vision mechanisms have been inspired by neuroscientific findings. However, with the focus on improving benchmark achievements, technical solutions have been shaped by application and engineering constraints. This includes the traini...

MedKPL: A heterogeneous knowledge enhanced prompt learning framework for transferable diagnosis.

Journal of biomedical informatics
Artificial Intelligence (AI) based diagnosis systems have emerged as powerful tools to reform traditional medical care. Each clinician now wants to have his own intelligent diagnostic partner to expand the range of services he can provide. However, t...

Ergonomic investigations on novel dynamic postural estimator using blaze pose and transfer learning.

Ergonomics
The aim is to develop a computer-based assessment model for novel dynamic postural evaluation using RULA. The present study proposed a camera-based, three-dimensional (3D) dynamic human pose estimation model using 'BlazePose' with a data set of 50,00...

Towards an Optimized Distributed Message Queue System for AIoT Edge Computing: A Reinforcement Learning Approach.

Sensors (Basel, Switzerland)
The convergence of artificial intelligence and the Internet of Things (IoT) has made remarkable strides in the realm of industry. In the context of AIoT edge computing, where IoT devices collect data from diverse sources and send them for real-time p...

Brain-optimized deep neural network models of human visual areas learn non-hierarchical representations.

Nature communications
Deep neural networks (DNNs) optimized for visual tasks learn representations that align layer depth with the hierarchy of visual areas in the primate brain. One interpretation of this finding is that hierarchical representations are necessary to accu...

DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Although graph representation learning has been studied extensively in static graph settings, dynamic graphs are less investigated in this context. This paper proposes a novel integrated variational framework called DYnamic mixture Variational Graph ...

The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research.

Research in social & administrative pharmacy : RSAP
Artificial Intelligence (AI) has revolutionized various domains, including education and research. Natural language processing (NLP) techniques and large language models (LLMs) such as GPT-4 and BARD have significantly advanced our comprehension and ...

ChatGPT in medical imaging higher education.

Radiography (London, England : 1995)
INTRODUCTION: Academic integrity among radiographers and nuclear medicine technologists/scientists in both higher education and scientific writing has been challenged by advances in artificial intelligence (AI). The recent release of ChatGPT, a chatb...

XRecon: An Explainbale IoT Reconnaissance Attack Detection System Based on Ensemble Learning.

Sensors (Basel, Switzerland)
IoT devices have grown in popularity in recent years. Statistics show that the number of online IoT devices exceeded 35 billion in 2022. This rapid growth in adoption made these devices an obvious target for malicious actors. Attacks such as botnets ...