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Artificial Intelligence and Public Health: An Exploratory Study.

International journal of environmental research and public health
Artificial intelligence (AI) has the potential to revolutionize research by automating data analysis, generating new insights, and supporting the discovery of new knowledge. The top 10 contribution areas of AI towards public health were gathered in t...

Lifelong Text-Audio Sentiment Analysis learning.

Neural networks : the official journal of the International Neural Network Society
Sentiment analysis refers to the mining of textual context, which is conducted with the aim of identifying and extracting subjective opinions in textual materials. However, most existing methods neglect other important modalities, e.g., the audio mod...

Hyper-Mol: Molecular Representation Learning via Fingerprint-Based Hypergraph.

Computational intelligence and neuroscience
With the development of artificial intelligence (AI) in the field of drug design and discovery, learning informative representations of molecules is becoming crucial for those AI-driven tasks. In recent years, the graph neural networks (GNNs) have em...

Implementation of Deep-Learning-Based CSI Feedback Reporting on 5G NR-Compliant Link-Level Simulator.

Sensors (Basel, Switzerland)
Advances in machine learning have widened the range of its applications in many fields. In particular, deep learning has attracted much interest for its ability to provide solutions where the derivation of a rigorous mathematical model of the problem...

Learning to Live with Strange Error: Beyond Trustworthiness in Artificial Intelligence Ethics.

Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees
Position papers on artificial intelligence (AI) ethics are often framed as attempts to work out technical and regulatory strategies for attaining what is commonly called In such papers, the technical and regulatory strategies are frequently analyzed...

Ten quick tips for sequence-based prediction of protein properties using machine learning.

PLoS computational biology
The ubiquitous availability of genome sequencing data explains the popularity of machine learning-based methods for the prediction of protein properties from their amino acid sequences. Over the years, while revising our own work, reading submitted m...

Vision-Based Topological Mapping and Navigation With Self-Organizing Neural Networks.

IEEE transactions on neural networks and learning systems
Spatial mapping and navigation are critical cognitive functions of autonomous agents, enabling one to learn an internal representation of an environment and move through space with real-time sensory inputs, such as visual observations. Existing model...

Transfer learning for genotype-phenotype prediction using deep learning models.

BMC bioinformatics
BACKGROUND: For some understudied populations, genotype data is minimal for genotype-phenotype prediction. However, we can use the data of some other large populations to learn about the disease-causing SNPs and use that knowledge for the genotype-ph...

Finding patterns in policy questions.

Scientific reports
To help advance exchanges between science and policy, a useful first step is to examine the questions which policymakers pose to scientists. The style of a question indicates what the asker is motivated to know, and how they might use that knowledge....

Multi-objective data enhancement for deep learning-based ultrasound analysis.

BMC bioinformatics
Recently, Deep Learning based automatic generation of treatment recommendation has been attracting much attention. However, medical datasets are usually small, which may lead to over-fitting and inferior performances of deep learning models. In this ...