D. Pamucar

Advancing Alzheimer’s Disease Prediction with Optimized Deep and Active Learning Approaches

Alzheimer’s Disease (AD) is a progressive neurological disorder primarily affecting cognitive and memory functions. Artificial Intelligence (AI)-based early detection systems are needed to address the increasing incidence of AD. However, the traditional detection systems suffer from several challenges, including clas...

An integrated decision-making framework for prioritizing the barriers and applications in medical digital twins under hesitant fuzzy linguistic environment with stochastic probabilistic distribution

The rapid evolution of digital twins (DTs) technology is reshaping the medical service system. As medical DTs (MDTs) are themselves complex, existing decisionmaking framework often ignored decision-makers’ (DMs’) hesitant fuzzy preference information and subjective cognitive biases. This research develops an integrated...

Challenge in Applying ChatGPT in Education: Evaluating Potential Drawbacks through Failure Modes and Effects Analysis and Logarithm Methodology of Additive Weights

An integrated LMAW–DNMA–FMEA framework is developed to identify, prioritize, and evaluate the most critical risks associated with ChatGPT adoption in higher education, indicating that overreliance on AI-generated content, degradation of critical thinking skills, and unreliable referencing represent the most significant...

Dynamic Replenishment Policies for Vendor-Managed Inventory under Stochastic Demand: A Simulation-Based Comparative Study

Vendor-Managed Inventory (VMI) is a pivotal strategy for optimizing supply chain performance, yet it poses a significant challenge in balancing operational costs against service levels under stochastic demand. While dynamic policies are gaining traction, literature lacks a systematic comparison of the underlying trigge...

An integrated framework for selecting augmented reality software to enhance occupational safety in the electro-energetic industry