Description
Măriuca-Roxana GAVRILOAIA, Sorina Nicoleta AURICĂ, Cristina Maria FĂCĂLEȚ, Mariana PANŢUROIU, Luiza CIMA, Luciana GĂLĂȚANU, Anton ALDEA, Iulian SÂRBU, Mirela Claudia RÎMBU
Artificial Intelligence (AI) is revolutionizing drug interaction analysis, providing healthcare with powerful tools to enhance patient safety and treatment outcomes. Traditional methods for identifying adverse drug interactions are often limited by manual processes and static databases, which can overlook complex patterns. AI addresses these limitations by employing machine learning, deep learning, and natural language processing to analyze vast datasets, identifying subtle interactions that might elude conventional analysis. AI-driven systems, increasingly implemented in hospitals, offer real-time monitoring of prescriptions, alerting medical professionals to potentially dangerous interactions and thus reducing adverse events. Despite the substantial benefits—such as increased accuracy, reduced workload, and improved patient safety—AI also faces challenges, including data privacy concerns and regulatory constraints. Furthermore, AI holds promise in advancing personalized medicine, where interaction analysis is tailored to individual genetic profiles and medical histories. By harnessing AI’s capabilities, the healthcare industry can move toward a future where drug interactions are predictively managed, ultimately creating a safer and more efficient healthcare environment. This article explores the applications, benefits, and challenges of AI in pharmacology, underscoring the need for ongoing research and collaboration in this transformative field.
Reviews
There are no reviews yet.