ClinicalStatAI: A Cloud-Based, AI-Augmented Platform for Accessible Survival Analysis in Healthcare

The integration of artificial intelligence (AI) into healthcare analytics has led to transformative progress across diagnostics, imaging, and population health. Yet, survival analysis—a critical domain in clinical outcomes research—continues to be hindered by complex methodologies and limited accessibility for non-programmers. We introduce https://stai.globalstatsol.com, a web-based platform designed to make survival analysis both accessible and interpretable through a no-code, modular interface. ClinicalStatAI currently supports widely used and validated statistical models, including the Cox Proportional Hazards model, the Weibull model, and the Log-normal model. These models are integrated with an AI interpretation layer powered by GPT-4.1, enabling natural language summaries and transparent diagnostic feedback. Initial validation using simulated datasets demonstrated strong performance and interpretability, with typical processing times under 30 seconds for mid-sized datasets. ClinicalStatAI provides a foundational step toward democratizing real-time health outcomes modeling by aligning statistical robustness with AI-assisted usability.