Through predictive modelling, AI supports target identification, prediction of physicochemical properties and formulation strategy selection.

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, ...

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 ...

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, ...

Forensic science plays a vital role in identifying, characterizing, and quantifying physical and biological traces recovered from crime scenes — a task that ...