Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...

Introduction Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate ...

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

That’s the aim of predictive cyber resilience (PCR)—an emerging approach to security built on intelligence, automation and ...

Abstract: Model predictive current control (MPCC) based on sliding mode disturbance observer (SMDO) effectively addresses the issues arising from parameter mismatches and unmodeled nonlinear elements ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Maritime transportation and offshore renewable energy systems form the backbone of sustainable ocean economies. As these infrastructures scale in complexity ...

Despite advanced algorithms and automation, one truth remains: Effective cybersecurity requires a careful balance between machine precision and human judgment.

Objective: To explore the risk factors of cognitive dysfunction in patients with leukoaraiosis (LA) and to construct a predictive model using machine learning. Methods: A total of 273 patients with LA ...

Future crime spots or potential perpetrators can be predicted with forecasts that are based on algorithms. Postdoctoral Researcher Carlo Gatti from the University of Turku in Finland studied the ...

Abstract: Accurate motion control in the face of disturbances within complex environments remains a major challenge in robotics. Classical model-based approaches often struggle with nonlinearities and ...