Related Experiment Video
Updated: Feb 24, 2026

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
Published on: April 12, 2021
The Role of AI in Patient Monitoring Using Smart Medical Devices: Opportunities and Challenges
Hamid Gholamhosseini1, Mirza Mansoor Baig2, Shereen Afifi3
1School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand,
Implementing Artificial Intelligence (AI) in patient monitoring via smart devices presents significant opportunities and challenges. A collaborative, holistic approach is essential for responsible AI integration in healthcare.
Area of Science:
- Healthcare Technology
- Artificial Intelligence in Medicine
- Digital Health
Background:
- Artificial Intelligence (AI) demonstrates rapid advancement and significant potential in healthcare.
- Patient monitoring using smart medical devices is a key area for AI integration.
- Personalized patient care plans (PPCP) can be enhanced through AI applications.
Purpose of the Study:
- To investigate the opportunities, challenges, and barriers of implementing AI in patient monitoring with smart medical devices.
- To provide a comprehensive analysis of AI integration in patient care settings.
- To identify strategies for maximizing AI benefits while mitigating risks in healthcare.
Main Methods:
- Literature review of studies on AI in patient care and personalized patient care plans.
- Analysis of current state, potential applications, benefits, and challenges of AI in healthcare.
- Examination of stakeholder roles and necessary frameworks for AI deployment.
Main Results:
- AI offers substantial opportunities for improving patient monitoring and personalized care.
- Key challenges include model explainability, validation, regulation, and privacy integration.
- A holistic approach involving diverse stakeholders is crucial for successful AI implementation.
Conclusions:
- Responsible AI deployment in healthcare requires prioritizing ethical considerations, patient privacy, and model transparency.
- Collaboration among technology developers, healthcare professionals, regulators, and end-users is vital.
- Developing robust frameworks is necessary to balance AI's benefits with its challenges in clinical workflows.
Related Concept Videos
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Current Trends in Nursing II
Pulse rhythm
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
Errors occurring during blood pressure monitoring
Several factors...
Holter Monitor: 24-Hour Monitoring

