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Tuesday, October 6
 

12:00 UTC

S112 - Predicting the Right Treatment for the Right Patient: An AI-Powered Decision Support Framework Based on Predicted Individual Treatment Effects
Tuesday October 6, 2026 12:00 - 12:30 UTC
Medical decisions—ranging from diagnosis to treatment selection—are inherently uncertain. Clinicians often rely on heuristic, experience-driven processes to integrate heterogeneous data. In this context, Predicted Individual Treatment Effects (PITE) offer a principled statistical framework to quantify how much a specific patient benefits from one treatment over another.

Advances in computational systems now enable machines to identify complex patterns within large datasets, facilitating a shift toward data-driven, individualized healthcare. This work explores using PITE to support clinical decision-making across diverse diseases and contexts. We address critical questions: which AI methods suit specific clinical datasets, how PITE should be validated, and how outcome complexity affects tool reliability.

We demonstrate PITE-based models in various disease settings, each posing unique methodological challenges. Our results show that even under real-world conditions—such as missing data—predictive models maintain interpretability and generate estimates that support clinicians. Notably, our findings highlight that internal validation is insufficient; external validation is essential for robust predictions.

Ultimately, effective PITE-based support requires more than modeling. It demands an adaptive, continuously learning system integrating data management, modeling strategies, regulatory-grade interpretability, and ongoing validation to translate evidence into precise.
Speakers
avatar for Pamela Solano

Pamela Solano

PhD Researcher, Faculty of Computer Science and Data Science, Regensburg University
I am Pamela Solano, a statistician and researcher at the University of Regensburg, Germany. Since 2014, I have worked as a biostatistician. Following my PhD in 2018, my research focus toward statistical modeling approaches with direct societal relevance. I began working in environmental... Read More →
Organizers
avatar for Pamela Solano

Pamela Solano

PhD Researcher, Faculty of Computer Science and Data Science, Regensburg University
I am Pamela Solano, a statistician and researcher at the University of Regensburg, Germany. Since 2014, I have worked as a biostatistician. Following my PhD in 2018, my research focus toward statistical modeling approaches with direct societal relevance. I began working in environmental... Read More →
Tuesday October 6, 2026 12:00 - 12:30 UTC
Zoom Room #1
 
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