Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, ...

Discover why the transition from AI chatbots to autonomous agents is raising alarms about data loss, action blindness, and ...

Modern credit risk management now leans significantly on predictive modelling, moving far beyond traditional approaches. As lending practices grow increasingly intricate, companies that adopt advanced ...

Traditional testing, though valuable, is often reactive and identifies quality issues only after they have occurred. This can lead to project delays and financial and reputational losses. In fact, ...

Zohar Bronfman is the cofounder and CEO of Pecan AI, a predictive analytics platform making advanced AI accessible to business teams. For decades, predictive analytics was a capability largely ...

Processing data closer to its source (edge computing) combined with AI allows for faster analysis and decision-making in preventative maintenance, as well as enhances data security. The work flows in ...