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Articles linked to this work by shared authors, journal, and citation graph.

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Artificial intelligence and innovation in hospital pharmacy: embracing opportunities.

European journal of hospital pharmacy : science and practice·2025
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[Translated article] Ethical aspects of AI in hospital pharmacy.

Farmacia hospitalaria : organo oficial de expresion cientifica de la Sociedad Espanola de Farmacia Hospitalaria·2025
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[Translated article] OrPhar-SEFH 2024-2027 Strategic Plan.

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Approaching artificial intelligence to Hospital Pharmacy.

Yared González-Pérez1, Alfredo Montero Delgado2, Jose Manuel Martinez Sesmero3

  • 1Servicio de Farmacia, Hospital Universitario de Canarias, San Cristóbal de La Laguna, España.

Farmacia Hospitalaria : Organo Oficial De Expresion Cientifica De La Sociedad Espanola De Farmacia Hospitalaria
|August 3, 2024
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances healthcare by analyzing patient data to improve decision-making. For hospital pharmacists, AI aids in identifying drug interactions and optimizing patient care.

Keywords:
Aprendizaje automáticoAprendizaje profundoArtificial intelligenceDeep learningFarmacia hospitalariaHospital pharmacyInteligencia ArtificialMachine learningNeuronal networks and natural language processingRedes neuronales y procesamiento natural del lenguaje

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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.