The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

A production-ready stock price prediction system using Bayesian Optimized LSTM models with advanced uncertainty quantification and multi-step forecasting capabilities. Stock_Price_Prediction/ ├── 🎯 ...

Kentaro Matsuura (2023). Bayesian Statistical Modeling with Stan, R, and Python. Singapore: Springer. URL: https://link.springer.com/book/10.1007/978-981-19-4755-1 ...

bDepartment of Radiation Oncology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan cDivision of Haematology and Oncology, Department of Internal Medicine, Tri-Service ...

Healthcare organizations have access to more data than ever before. Whereas in the past they were mostly limited to data from labs and electronic data capture (EDC) systems, they now have vast swaths ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

For whom? The events are open to all interested, within or outside of KI. The events are free of charge. The program is tailored towards users of statistics (but you don’t need to be a statistician), ...