AI-DRIVEN INNOVATIONS IN HEALTHCARE AND PHARMACEUTICAL SCIENCES

Abstract

Artificial Intelligence (AI) is changing healthcare by making data management, diagnostics, treatment personalization, patient monitoring, and operations more effective. Technologies like machine learning, deep learning, natural language processing, and predictive analytics are helping with everything from drug discovery and hospital pharmacy to automated diagnostic tools such as MRI and CT imaging. For example, AI-assisted radiology is enhancing the accuracy of MRI and CT scan interpretations, reducing diagnostic errors, and speeding up turnaround times. Predictive analytics in patient monitoring systems can foresee potential health deteriorations, allowing proactive interventions. Still, using AI in healthcare comes with challenges, such as data privacy and security, ethical and legal issues, interoperability, and the difficulties of working with both humans and AI. Many healthcare professionals and members of the public are also hesitant to accept AI because of worries about safety, reliability, and access. This study reviews how AI is used in healthcare, its benefits, and the barriers to putting it into practice. It points out the importance of working across disciplines, continuing research and development, and improving AI education for healthcare workers to get the most out of AI in healthcare. The review also gives guidance for stakeholders as they adapt to the changing role of AI in healthcare.