Quantum machine learning enablement for life sciences - Laia Domingo
Year: 2025
Type: article
Abstract: This talk presents quantum machine learning (QML) enablement as a practical pathway toward real-world impact in healthcare and life sciences. At Ingenii, we develop tools and research to help data scientists explore and apply quantum computing to complex problems in biology and medicine. Our ecosystem combines hands-on educational programs, an open-source QML Python library, and a use case validation platform that guides teams from exploration to proof of concept. We will also present three research projects: drug discovery, where hybrid quantum neural networks accelerate training and improve predictive performance; medical imaging, where quantum optimization enables accurate image segmentation without labeled data; and clinical trial optimization, where quantum methods enhance patient stratification and biomarker selection to reduce bias and improve trial efficiency. Together, these advances illustrate how quantum computing can already start transforming life sciences today.
Author: Domingo, Laia
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7106040109
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