Advancing Point-of-Care Testing by Application of Machine Learning Techniques and Artificial Intelligence

Area of Science:

• Healthcare technology
• Artificial intelligence in medicine

Background:

• Artificial intelligence (AI) shows promise for improving diagnosis and management of various health conditions.
• Point-of-care testing expands healthcare access beyond traditional settings.
• Effective collaboration is key to addressing clinical challenges.

Purpose of the Study:

• To highlight the potential of artificial intelligence in healthcare.
• To emphasize the importance of collaboration in developing AI solutions.
• To advocate for clear terminology in research for better collaboration.

Main Methods:

• Literature review on AI in healthcare and point-of-care testing.
• Analysis of collaboration models between developers, clinicians, and end-users.
• Discussion on the role of standardized terminology in research.

Main Results:

• AI is recognized for its potential to enhance diagnosis and management of diseases.
• Point-of-care testing improves healthcare accessibility.
• Collaboration and clear communication are vital for successful clinical problem-solving using AI.

Conclusions:

• AI holds significant promise for transforming healthcare delivery.
• Interdisciplinary collaboration and standardized terminology are essential for realizing AI's full potential in clinical practice.