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All Outputs (249)

Explore the relationship between house prices and crime rate in the UK using machine learning techniques (2025)
Journal Article

In the UK, house price estimation is an important topic. It has been discussed in numerous academic research publications and official and business reports. A house’s price can change depending on size, age, and location. One of the main characterist... Read More about Explore the relationship between house prices and crime rate in the UK using machine learning techniques.

From accuracy to vulnerability: Quantifying the impact of adversarial perturbations on healthcare AI models (2025)
Journal Article

As AI becomes indispensable in healthcare, its vulnerability to adversarial attacks demands serious attention. Even minimal changes to the input data can mislead Deep Learning (DL) models, leading to critical errors in diagnosis and endangering patie... Read More about From accuracy to vulnerability: Quantifying the impact of adversarial perturbations on healthcare AI models.

A flexible software-defined networking-based privacy-preserving method for Internet of Things-based Smart City environment based on the neighbors situation (2025)
Journal Article

We introduce “DPSmartCity,” a context-aware dynamic software-defined networking (SDN) framework that preserves privacy in smart cities. Enhancing the Internet of Things (IoT)-centric infrastructure with dynamic network management, the SDN controller... Read More about A flexible software-defined networking-based privacy-preserving method for Internet of Things-based Smart City environment based on the neighbors situation.

Federated learning in IoT environments: Examining the three-way see-saw for privacy, model-performance, and network-efficiency (2025)
Journal Article

This survey paper provides an in-depth exploration of Federated Learning (FL) in Internet of Things (IoT) environments , focusing on privacy-preserving techniques and their influence on model performance and network efficiency. It highlights key chal... Read More about Federated learning in IoT environments: Examining the three-way see-saw for privacy, model-performance, and network-efficiency.

Defining the recommended gray zone in MGMT promoter methylation pyrosequencing reporting: A robust translatable method to implement new EANO guidelines (2025)
Journal Article

Background
The DNA repair protein O6-methylguanine-DNA methyltransferase (MGMT) may cause resistance of tumour cells to alkylating agents, and is a predictive biomarker in high-grade gliomas treated with temozolomide. Recent EANO guidelines recommen... Read More about Defining the recommended gray zone in MGMT promoter methylation pyrosequencing reporting: A robust translatable method to implement new EANO guidelines.

Inter-rater reliability of stress signatures in exfoliated primary dentition - Improving scientific rigor and reproducibility in histological data collection (2025)
Journal Article

Accentuated Lines (ALs) in tooth enamel can reflect metabolic disruptions from physiological or psychological stresses during development. They can therefore serve as a retrospective biomarker of generalized stress exposure in archaeological and clin... Read More about Inter-rater reliability of stress signatures in exfoliated primary dentition - Improving scientific rigor and reproducibility in histological data collection.

Time series forecasting for air quality with structured and unstructured data using artificial neural networks (2025)
Journal Article

Various machine learning algorithms exist to predict air quality, but they can only analyse structured data gathered from monitoring stations. However, the concentration of certain pollutants, such as PM2.5 and PM10, can be visually significant when... Read More about Time series forecasting for air quality with structured and unstructured data using artificial neural networks.

AI under attack: Metric-driven analysis of cybersecurity threats in deep learning models for healthcare applications (2025)
Journal Article

Incorporating Artificial Intelligence (AI) in healthcare has transformed disease diagnosis and treatment by offering unprecedented benefits. However, it has also revealed critical cybersecurity vulnerabilities in Deep Learning (DL) models, which rais... Read More about AI under attack: Metric-driven analysis of cybersecurity threats in deep learning models for healthcare applications.