Artificial Intelligence applied to care (I): Origin and general concepts.

Area of Science:

• Healthcare Informatics
• Artificial Intelligence Applications
• Nursing Science

Background:

• The rise of Artificial Intelligence (AI), particularly Generative AI like ChatGPT, has increased its presence in professional settings.
• AI encompasses a broad range of techniques beyond generative models, including those vital for data analysis and decision support in healthcare.
• Ensuring transparency and explainability in AI predictive models is essential for healthcare professionals to trust and adopt these technologies.

Purpose of the Study:

• To provide a comprehensive overview of predictive Artificial Intelligence techniques applicable to the nursing care process.
• To illustrate these techniques with practical healthcare examples for better understanding by nursing professionals.
• To discuss the limitations and future prospects of AI in nursing care.

Main Methods:

• Exploration of data-centric AI methods: Machine Learning, Deep Neural Networks, and Generative Artificial Intelligence.
• Description of process-centric AI techniques: Predictive Process Monitoring.
• Inclusion of practical healthcare-based examples for each technique.

Main Results:

• Summary of key predictive AI techniques relevant to nursing care.
• Demonstration of how Machine Learning, Deep Neural Networks, Generative AI, and Predictive Process Monitoring can be applied in healthcare settings.
• Identification of the advantages and disadvantages of these AI approaches.

Conclusions:

• Predictive AI techniques offer significant potential to enhance the nursing care process.
• Increased understanding and transparency of AI methods are vital for their successful integration into clinical practice.
• Further research and development are needed to address the limitations and fully realize the prospects of AI in nursing.