Quantum machine learning enablement for life sciences - Laia Domingo

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.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-06
DOI
https://doi.org/10.5281/zenodo.17643101
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantum machine learning enablement for life sciences - Laia Domingo

Zenodo (CERN European Organization for Nuclear Research)
Quantum Computing Algorithms and Architecture
article

Quantum machine learning enablement for life sciences - Laia Domingo

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Responsible consumption and production
Openalex Percentile: Top 22%
Quantum Computing Algorithms and Architecture
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