Parkinson’s disease (PD) is the second most common neurodegenerative disorder worldwide, predominantly affecting older adults. Early detection is crucial, as subtle motor and non-motor symptoms frequently overlap with other conditions, often resulting in delayed diagnosis. Many existing models rely on costly and less accessible imaging modalities such as MRI or PET scans, limiting their applicability in resource-constrained settings where only routine clinical data are available. This study develops interpretable AI models for early PD detection using structured clinical variables, incorporating feature selection techniques. Feature selection was conducted via Random Forest (RF) importance... More >

Hypertension, a life-threatening global health challenge, requires early detection to prevent severe cardiovascular complications. Fundus imaging reveals microvascular alterations, yet conventional diagnosis often misses subtle early changes. This study introduces a multimodal deep learning framework that integrates clinical data, fundus images, and demographic features to improve hypertension prediction. Unlike single-modality approaches, our method captures complementary risk factors from both structured and unstructured data. We evaluate machine learning and deep learning models on clinical data, confirming DL's superior accuracy. For fundus images alone, a CNN achieves 74.44% accuracy, h... More >

The Industrial Internet of Things (IIoT) is a foundational pillar of Industry 4.0, enabling real-time data exchange and automation through the integration of smart sensors, actuators, and networked machinery. While this interconnectivity enhances operational efficiency and decision-making on the industrial floor, it also introduces complex cybersecurity challenges. This work reviews literature related to the IIoT with a focus on threat modeling techniques, including mitigation strategies. It comprises the theoretical frameworks and the implemented solutions within the domains of critical infrastructure and manufacturing. The coexistence of legacy control software systems, stringent real-time... More >