Background and Aim: Biomedical engineering and artificial intelligence (AI) are closely connected fields with significant potential for innovation and advancement in the field of medicine. This review paper explores the intersection of biomedical engineering and AI in medicine.
Method: The review conducted a comprehensive analysis of articles published between 2003-2023 to explore the use of AI in healthcare. A total of 54 articles were selected based on inclusion criteria, and data were extracted independently by reviewers. The findings were synthesized qualitatively, identifying common themes and patterns in the effectiveness of AI in healthcare. The quality of the studies was assessed using relevant tools, excluding those with a high risk of bias or methodological limitations.
Results: The paper highlights the potential of AI to transform healthcare by analyzing and processing large amounts of medical data, leading to improved diagnosis, treatment, and personalized care. Machine learning algorithms, a subset of AI, can identify patterns and relationships in data that would be difficult for humans to discern. AI is currently being used in medical imaging, analysis of medical images, and the development of predictive models for disease diagnosis and therapeutic response.
Conclusion: The conclusion highlights the need for ethical guidelines and a legal framework for the use of AI in medicine. It emphasizes that AI should complement traditional medicine rather than replace it. The paper suggests that addressing these concerns and providing training and education to healthcare professionals will be crucial for the successful integration of AI in healthcare.