Approaching artificial intelligence to Hospital Pharmacy

Area of Science:

• Biomedical Informatics
• Health Informatics
• Computational Medicine

Background:

• Artificial intelligence (AI) involves computers performing human-like intelligent tasks.
• AI leverages large healthcare datasets to identify patterns and predict outcomes.
• Key AI methods include machine learning, deep learning, neural networks, and natural language processing.

Purpose of the Study:

• To explore the application and impact of AI in biomedicine and healthcare.
• To highlight the role of AI in improving pharmaceutical care and patient outcomes.
• To emphasize the transformative potential of AI for hospital pharmacists.

Main Methods:

• Utilizing AI algorithms and Machine Learning for data analysis.
• Analyzing extensive patient data, including medical records and medication profiles.
• Applying AI to identify drug-drug interactions and assess medication safety and efficacy.

Main Results:

• AI accelerates biomedical processes, enhances safety, and improves patient care.
• Hospital pharmacists can make more informed recommendations using AI-driven insights.
• AI integration leads to optimized pharmaceutical care processes and improved research.

Conclusions:

• AI is revolutionizing healthcare by enabling data-driven decision-making.
• Hospital pharmacists equipped with AI skills are pivotal in advancing pharmaceutical care.
• AI integration promises enhanced quality, efficiency, and innovation in pharmaceutical practice.