Enhancing Microsurgery Outcomes Data with High-Quality Synthetic Data Generated Using Artificial Intelligence: A Proof-of-Concept Study
Berk Barış Özmen, Graham S. Schwarz · Plastic & Reconstructive Surgery Global Open · 2024
Background: The potential of artificial intelligence (AI) in improving surgical outcomes through predictive modeling is greatly hindered by the scarcity of large datasets, especially in specialized surgical subdisciplines such as microsurgery. Synthetic data, statistically designed to mimic real world data with AI techniques, offers an innovative solution to overcome this challenge, enabling the generation of larger datasets from a limited number of cases. Methods: We utilized Generative Adversarial Networks (GANs), an AI model using Python and TensorFlow to expand our single institute immediate lymphatic reconstruction dataset comprised of 133 cases with pre-operative, intra-operative and post-operative features. The dataset underwent comprehensive preprocessing, including normalization and one-hot encoding aimed to create a more suitable data for the model to operate effectively. A GAN was then trained on this data to generate a synthetic dataset that mimics the statistical properties of the original dataset. Results: The GAN model was successful in generating a synthetic dataset of a total of 10,000 cases, significantly expanding the size of the original dataset while maintaining the statistical properties of the original dataset. Conclusion: This enhanced dataset provides a powerful tool for AI-driven predictive modeling aimed at improving surgical outcomes. Our study underscores the potential of AI and GANs in generating synthetic surgical outcomes data in microsurgery. By significantly expanding the size of the original dataset, we have improved its utility for AI-driven predictive modeling, paving the way for advanced research aimed at improving surgical outcomes. Future work could involve refining the synthetic data generation process to capture specific features of interest in microsurgery.