Traditional drug development relies on empirical trial-and-error screening processes rather than predictive computational modeling

General research and information gathering from multiple sources

Artificial intelligence applications across healthcare, covering clinical decision support, diagnostics, workflow automation, drug discovery, patient monitoring, safety risks, equity concerns, and regulation.