[Translated article] Introducing artificial intelligence to hospital pharmacy departments

Area of Science:

• Biomedical Informatics
• Computational Biology
• Health Services Research

Background:

• Artificial intelligence (AI) involves computers performing human-like intelligent tasks.
• AI algorithms leverage 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 artificial intelligence in biomedicine and pharmaceutical care.
• To highlight how AI can enhance decision-making for healthcare professionals, particularly hospital pharmacists.
• To outline the transformative potential of AI in improving pharmaceutical services and patient outcomes.

Main Methods:

• Utilizing artificial intelligence algorithms and machine learning to analyze extensive patient data.
• Processing diverse data types including medical records, laboratory results, and medication profiles.
• Employing AI for pattern recognition, outcome prediction, and process optimization.

Main Results:

• AI accelerates biomedical processes, enhances accuracy, and improves efficiency.
• Hospital pharmacists can identify drug-drug interactions and assess medication safety/efficacy using AI.
• AI facilitates informed recommendations, leading to better patient care and optimized pharmaceutical processes.

Conclusions:

• Artificial intelligence integration promises to elevate the quality of pharmaceutical care.
• AI adoption will optimize healthcare processes, foster research, and support open innovation.
• Hospital pharmacists equipped with AI expertise are pivotal in driving healthcare transformation.