Scientific
Publications
RARTAI is committed to advancing the frontier of Medical AI through rigorous academic research. Our published works span across deep learning applications in clinical diagnostics, predictive modeling, and ethical AI implementation in healthcare environments.
Multi-modal Neural Networks for Early Detection of Neurodegenerative Disorders
Chen, A., Stark, R., Ming, L., et al. (2024). Journal of Medical AI Systems, Vol. 12, Issue 4.
This study introduces a novel transformer-based architecture that integrates MRI imaging data with clinical speech patterns to identify early biomarkers of Parkinson's Disease with 94.2% accuracy.
Quantifying Uncertainty in Real-time Surgical Assistant Systems
Jones, S., & Gupta, K. (2023). Nature Healthcare Robotics, 15(2), 210-225.
Evaluating the application of Bayesian neural networks in high-stakes robotic surgery to provide confidence intervals for autonomous anatomical recognition tasks.
Privacy-Preserving Federated Learning for Rare Disease Data Synthesis
Wilson, D., Rossi, E., & Thorne, M. (2023). Computational Medicine Review, Vol. 9.
A framework for training robust diagnostic models across decentralized hospital networks without direct data sharing, specifically targeting orphan diseases with limited local datasets.