Periodic maintenance is common too, but still inefficient and often based on time, not actual machine condition. That ...

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...

Abstract: The integration of artificial intelligence (AI) in healthcare has facilitated new predictive analytics, assisting clinicians in making more accurate decisions based on data, rather than ...

As global business analytics transitions from descriptive dashboards to autonomous, agentic systems, Indian enterprises are confronting a structural question: can AI drive decisions at the pace ...

As organizations integrate data-driven insights into their operations, predictive screening models are emerging as both a ...

Tools Market is primarily driven by rapid digital transformation across industries, increasing adoption of generative AI, and the growing need for intelligent ...

Opinion: Embedding generative artificial intelligence into a law firm’s operations can enable it to become more competitive ...

Abstract: The recent integration of Machine Learning (ML) and sensor technologies in healthcare, particularly for diagnosing Major Depressive Disorder (MDD), has paved the way for advanced predictive ...

Generative tools may eventually reshape creative workflows, but predictive, optimization and data-driven AI are already reshaping business fundamentals.

The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based defenses have ...

During model development, it is essential to focus on model quality, including reducing bias risk, designing appropriate sample sizes, conducting external validation, and ensuring model ...