Research Radar

The Capacity and Robustness Trade-Off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting

119

Predictions of steel price indices through machine learning for the regional northeast Chinese market

146

ECON-ESG factors on energy efficiency: Fostering sustainable development in ECON-growth-paradox countries

101

Self-designed portable dual-mode fluorescence device with custom python-based analysis software for rapid detection via dual-color FRET aptasensor with IoT capabilities

114

Aggregator-Network Coordinated Peer-to-Peer Multi-Energy Trading via Adaptive Robust Stochastic Optimization

Advancements in current one-size-fits-all therapies compared to future treatment innovations for better improved chemotherapeutic outcomes: a step-toward personalized medicine

Using clusterProfiler to characterize multiomics data

960

Optimizing renewable energy systems through artificial intelligence: Review and future prospects

The global transition toward sustainable energy sources has prompted a surge in the integration of renewable energy systems (RES) into existing power grids. To improve the efficiency, reliability, and economic viability of these systems, the syner...

314

Worldwide trends in diabetes prevalence and treatment from 1990 to 2022: a pooled analysis of 1108 population-representative studies with 141 million participants

637

Smallholder farmers’ challenges and opportunities: Implications for agricultural production, environment and food security

155

AI-driven innovations in Alzheimer's disease: Integrating early diagnosis, personalized treatment, and prognostic modelling

131

Blockchain-Based Renewable Energy Trading Using Information Entropy Theory

A Review on the emerging technology of TinyML

Tiny Machine Learning (TinyML) is an emerging technology proposed by the scientific community for developing autonomous and secure devices that can gather, process, and provide results without transferring data to external entities. The technology...

A Survey of Graph Neural Networks for Social Recommender Systems

Social recommender systems (SocialRS) simultaneously leverage the user-to-item interactions as well as the user-to-user social relations for the task of generating item recommendations to users. Additionally exploiting social relations is clearly ...

166

Deep Multimodal Data Fusion

Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data (e.g., images, texts, or data collected from different sensors), feature engineering (e.g., extraction, combination/fusion), and decision-making (e.g., ...

270

Security, Privacy, and Decentralized Trust Management in VANETs: A Review of Current Research and Future Directions

Vehicular Ad Hoc Networks (VANETs) are powerful platforms for vehicular data services and applications. The increasing number of vehicles has made the vehicular network diverse, dynamic, and large-scale, making it difficult to meet the 5G network’...

101

Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey

Time Series Classification and Extrinsic Regression are important and challenging machine learning tasks. Deep learning has revolutionized natural language processing and computer vision and holds great promise in other fields such as time series ...

169

Pre-Trained Language Models for Text Generation: A Survey

Text Generation aims to produce plausible and readable text in human language from input data. The resurgence of deep learning has greatly advanced this field, in particular, with the help of neural generation models based on pre-trained language ...

157

Lightweight Deep Learning for Resource-Constrained Environments: A Survey

Over the past decade, the dominance of deep learning has prevailed across various domains of artificial intelligence, including natural language processing, computer vision, and biomedical signal processing. While there have been remarkable improv...

148

Academic Publication • Published Oct 28, 2024

Large Language Model Influence on Diagnostic Reasoning

ImportanceLarge language models (LLMs) have shown promise in their performance on both multiple-choice and open-ended medical reasoning examinations, but it remains unknown whether the use of such tools improves physician diagnostic reasoning.Obje...

440