Academic Articles & Research Papers

A Review of Fundamental Optimization Approaches and the Role of AI Enabling Technologies in Physical Layer Security

With the proliferation of 5G mobile networks within next-generation wireless communication, the design and optimization of 5G networks are progressing in the direction of improving the physical layer security (PLS) paradigm. This phenomenon...

Artificial intelligence assisted 3D in the robotic urooncology? A systematic review and narrative synthesis of current applications, challenges and future directions

Background: Artificial intelligence (AI)-assisted three-dimensional (3D) surgical platforms, integrated with augmented reality, have the potential to improve intraoperative anatomical recognition and provide surgeons with an immersive, dyna...

Raman Spectroscopy Pre-Trained Encoder: A Self-Supervised Learning Approach for Data-Efficient Domain-Independent Spectroscopy Analysis

Deep-learning methods have boosted the analytical power of Raman spectroscopy, yet they still require large, task-specific, labeled datasets and often fail to transfer across application domains. The study explores pre-trained encoders as a...

Sparsity Increases Uncertainty Estimation in Deep Ensemble

Deep neural networks have achieved almost human-level results in various tasks and have become popular in the broad artificial intelligence domains. Uncertainty estimation is an on-demand task caused by the black-box point estimation behavi...

Prediction of irinotecan toxicity in metastatic colorectal cancer patients based on machine learning models with pharmacokinetic parameters

Irinotecan (CPT-11) is a drug used against a wide variety of tumors, which can cause severe toxicity, possibly leading to the delay or suspension of the cycle, with the consequent impact on the prognosis of survival. The main goal of this w...

Development of machine learning models for predicting delirium in elderly patients after thoracic surgeries.

Tachyon: Enhancing stacked models using Bayesian optimization for intrusion detection using different sampling approaches

The integration of sensors in the monitoring of essential bodily measurements, air quality, and energy consumption in buildings demonstrates the importance of the Internet of Things (IoT) in everyday life. These security breaches are caused...

Comparative Evaluation of Artificial Intelligence-Generated Physician-Level Educational Content in Diabetic Foot Ulcers: Quality, Guideline Concordance, and Clinical Reliability

The study aimed to evaluate the quality, clinical reliability, and guideline concordance of physician-level educational responses generated by artificial intelligence (AI) in diabetic foot ulcer management. A blinded, comparative analysis w...

Convergence of Artificial Intelligence and Wearables in Strength Training and Performance Monitoring: A Scoping Review

Background: Strength training (ST) is essential for enhancing athletic performance and reducing injury risk, yet traditional monitoring relies heavily on subjective assessment, limiting objective and individualized evaluation. Objective: Th...

Identification of Aspergillus at section and species levels by artificial intelligence-based microscopic morphology image recognition

ABSTRACT Rapid and accurate identification of Aspergillus species in clinical microbiology laboratories is crucial for aspergillosis diagnosis and antifungal therapy. However, traditional methods still face challenges in distinguishing phyl...

Artificial Intelligence

"Machines who think—how utterly preposterous," huff beleaguered humanists, defending their dwindling turf. "Artificial Intelligence—it's here and about to surpass our own," crow techno-visionaries, proclaiming dominion. It's so simple and o...

Managing artificial intelligence

By the time you finish reading this editorial about artificial intelligence (AI), it will be outdated; the AI field is growing beyond the imagination of many. One cannot even look at the news without finding something about AI: duplication ...

Electromagnetic Field Distribution Mapping: A Taxonomy and Comprehensive Review of Computational and Machine Learning Methods

Electromagnetic field (EMF) exposure mapping is increasingly important for ensuring compliance with safety regulations, supporting the deployment of next-generation wireless networks, and addressing public health concerns. While numerous su...

A comprehensive review of explainable AI for disease diagnosis

Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited due to the transparency issue, which is considered ...

Membrane surface wettability and roughness under operating conditions and their implications for membrane performance

Membrane wettability is an important factor influencing separation efficiency, fouling resistance, water flux, and durability. Although membrane wetting has been extensively studied, few reviews have quantitatively examined the relationship...

Is cardiovascular risk profiling from UK Biobank retinal images using explicit deep learning estimates of traditional risk factors equivalent to actual risk measurements? A prospective cohort study design

Objective Despite extensive exploration of potential biomarkers of cardiovascular diseases (CVDs) derived from retinal images, it remains unclear how retinal images contribute to CVD risk profiling and how the results can inform lifestyle m...

Artificial Intelligence with Uncertainty

The information deluge currently assaulting us in the 21st century is having a profound impact on our lifestyles and how we work. We must constantly separate trustworthy and required information from the massive amount of data we encounter ...

A virtual physicist framework integrating dose prediction and large language models for automated treatment planning.

A multi-branch network for cooperative spectrum sensing via attention-based and CNN feature fusion

Abstract In cognitive radio (CR) systems, the accurate detection of spectrum holes is a cornerstone for efficient spectrum utilization. However, the increasing complexity of CR environments, particularly those with multiple primary users (P...

REVIEW OF THEORETICAL APPROACHES TO USING OF ARTIFICIAL INTELLIGENCE FOR PLANNING PROBLEMS IN ECONOMICS

Artificial intelligence methods and technologies are increasingly included in human's everyday life. Managing actors in the context of their activities, from the planning stage to the decision-making stage, are faced with the need to operat...