Academic Articles & Research Papers

Times are changing but order matters: transferable prediction of small-molecule liquid chromatography retention times.

From Design to Bedside: Brain-Targeted Engineered Nanoparticles and Predictive Modeling for Neurodegenerative Diseases Therapeutics.

AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness

This research evaluates the use of artificial intelligence to enhance the accuracy of predictions for mixed-mode I/III fracture toughness in polymethyl methacrylate . Traditionally, assessing fracture toughness relies heavily on destructive...

IEEE Access Special Section Editorial: 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility

Increasing urbanization is one major trend that shapes tomorrow’s society; by 2050, more than 85% of the developed world’s population will live in a comparatively small number of ever-growing cities. Within such cities ...

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

A physics-informed spatiotemporal graph neural network for photovoltaic power forecasting and micro-anomaly localization

Accurate power forecasting and precise fault diagnosis are critical for the reliable operation of large-scale photovoltaic systems. However, existing data-driven models often fail to capture complex spatiotemporal dependencies and lack phys...

A review of prediction methods for moving target trajectories

With the rapid emergence of mobile terminal equipment in intelligent transportation system, the deep understanding and accurate prediction of moving target trajectories are capable of reducing the traffic accident probability, and promoting...

Artificial intelligence and the future of global health

Concurrent advances in information technology infrastructure and mobile computing power in many low and middle-income countries (LMICs) have raised hopes that artificial intelligence (AI) might help to address challenges unique to the field...

Artificial intelligence: foundations of computational agents

Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. Artificial Intelligence: Foundations of Computational Agents is a textbook aimed at junior to senior undergraduate stude...

Application of artificial intelligence to the electrocardiogram

Artificial intelligence (AI) has given the electrocardiogram (ECG) and clinicians reading them super-human diagnostic abilities. Trained without hard-coded rules by finding often subclinical patterns in huge datasets, AI transforms the ECG,...

Artificial Intelligence with Uncertainty

This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural la...

Current Signature-Based Bearing Fault Severity Classification Using a Robust Multilevel Cascaded Framework

Bearing faults are a critical concern in electrical machines, particularly permanent magnet synchronous motors (PMSMs), commonly used in electric vehicles. Early and accurate classification of bearing fault severity is essential for predict...

An Instructional Optimization Method Based on Bidirectional Transformer and Reinforcement Learning

With the rapid development of information technology, personalized education has become a key direction for improving the quality of online learning and optimizing individualized learning paths. However, accurately recommending appropriate ...

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties ...

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

Abstract Background Homologous recombination deficiency (HRD) is recognized as a pan-cancer predictive biomarker that potentially indicates who could benefit from treatment with PARP inhibitors (PARPi). Despite its clinical significance, HR...

Expert system for managing data on the competencies of a modern manager

In the modern economy, digitalization has become one of the key components of the Russian Federation regions socio-economic development. Enterprises of various industries are faced with the need to process large amounts of data, which great...

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. Howeve...

A satellite-derived, ground-measurement-independent monthly PM2.5 mass concentration dataset over China during 2000 - 2015

Following the accelerated development of urbanization and industrialization, atmospheric particulate matter has become a significant threat to public health globally. Environmental health studies usually use the mass concentration of fine p...

Artificial Intelligence and Acute Stroke Imaging

Artificial intelligence technology is a rapidly expanding field with many applications in acute stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute stroke is critical for initiating prompt intervention ...

Economic Policy for Artificial Intelligence

Recent progress in artificial intelligence (AI)—a general purpose technology affecting many industries—has been focused on advances in machine learning, which we recast as a quality-adjusted drop in the price of prediction. How will this sh...