References on Leveraging AI Models for Synthetic Data Generation in Healthcare
In recent years, there has been a significant increase in the use of artificial intelligence (AI) and generative models in healthcare, particularly in the generation of synthetic data. One such study by Jadon A and Kumar S, titled “Leveraging Generative AI Models for Synthetic Data Generation in Healthcare: Balancing Research and Privacy,” explored the potential of using AI models to generate synthetic data in healthcare settings. This research, published in arXiv in 2023, sheds light on the challenges and opportunities of using generative AI models for data generation in the healthcare sector.
Synthetic data generation has emerged as a promising solution to address data privacy concerns while still enabling researchers to train and validate AI models effectively. By using generative AI models, researchers can create synthetic datasets that mimic real data characteristics without compromising patient privacy. This approach allows researchers to overcome the limitations of using real patient data, such as data scarcity, privacy regulations, and data bias.
The study by Jadon A and Kumar S highlights the importance of balancing research goals with privacy concerns when leveraging generative AI models for healthcare data generation. It emphasizes the need for robust guidelines and ethical considerations to ensure that synthetic data generation in healthcare is conducted responsibly and in accordance with data privacy regulations.
Furthermore, the study by Jadon A and Kumar S aligns with existing research in the field of AI and healthcare, such as concerns related to artificial intelligence, challenges and prospects of deep learning, and the potential applications of AI in dentistry. These studies underscore the importance of addressing biases, ensuring fairness, and promoting transparency in AI applications in healthcare.
In conclusion, the research by Jadon A and Kumar S provides valuable insights into the use of generative AI models for synthetic data generation in healthcare. By exploring the balance between research goals and privacy concerns, this study contributes to the ongoing discussion on the ethical and responsible use of AI in healthcare. As technology continues to evolve, it is essential to consider the ethical implications and societal impact of AI applications in healthcare, ensuring that these technologies benefit patients and society as a whole.