Classiq & UC Chile Launch 12-Month Quantum Pathology Research

Classiq and Pontificia Universidad Católica de Chile (UC Chile) have launched a 12-month research project focused on applying hybrid quantum algorithms to biomedical image analysis, a collaboration funded by Avanza UC. The project, titled “Enhancing Pathology through Quantum Computing,” initially targets renal pathology, addressing a significant public health issue in Chile and throughout Latin America by leveraging quantum machine learning for kidney lesion classification and automated image segmentation. To the collaborators’ knowledge, this is the first consortium in Latin America to combine quantum computing, machine learning, and computational pathology. Nir Minerbi, CEO and co-founder of Classiq, said that Latin America has the scientific talent, institutional momentum and public health needs to support this next stage of quantum computing applications; the project aims to strengthen the regional quantum ecosystem while exploring practical research paths for health innovation.

Classiq & UC Chile Launch Biomedical Image Analysis Research

This project focuses on renal pathology, a significant and increasing public health concern throughout Chile and the broader region, rather than theoretical explorations. Researchers will apply quantum machine learning techniques to computational pathology, initially concentrating on kidney lesion classification, automated glomerular segmentation, and comprehensive analysis of histological slides. The team’s approach leverages curated datasets provided by Fundação Oswaldo Cruz (FIOCRUZ) and Universidade Federal da Bahia (UFBA) in Brazil, integrating expertise in digital pathology, computer vision, and biomedical data analysis with quantum computing capabilities. Dr. Dardo Goyeneche of UC Chile’s Faculty of Physics will lead the project, building upon his work as founder and director of QuDIT, a quantum information theory group with over 20 students, and director of Project QuAntü, Chile’s first universal quantum computer initiative. The research will utilize Classiq’s quantum software platform alongside the NVIDIA CUDA-Q platform, facilitating a streamlined workflow from algorithm development to execution and simulation. Dr. Goyeneche explained that this project connects fundamental quantum research with an important biomedical challenge, emphasizing the creation of a regional platform for quantum machine learning in health.

Hybrid Quantum Algorithms for Renal Pathology Applications

The convergence of quantum computing and machine learning is rapidly shifting from theoretical possibility to practical application, with a growing emphasis on biomedical challenges. This area represents a significant public health issue not only in Chile, but throughout Latin America, providing a regionally relevant focus for the development of novel diagnostic tools. Researchers are actively exploring hybrid quantum algorithms, combining the strengths of both classical machine learning and emerging quantum capabilities. The project, spearheaded by Dr. Goyeneche, advances scientific understanding and addresses a real-world need.

This collaboration brings together quantum software engineering, machine learning and biomedical data expertise in a workflow and project that can help strengthen the regional quantum ecosystem while exploring a practical research path for health.

NVIDIA CUDA-Q & Classiq Platform for Algorithm Development

Researchers are increasingly leveraging specialized software platforms to accelerate the development of quantum algorithms, and the collaboration between UC Chile and Classiq exemplifies this trend through the integration of NVIDIA CUDA-Q. This pairing allows for a seamless transition between abstract quantum concepts and concrete computational steps, a critical factor in translating research into tangible results. Selected algorithms will then be simulated on NVIDIA AI infrastructure and tested on IonQ quantum hardware, allowing for direct comparison with classical machine learning techniques. This benchmarking process, utilizing standard computer vision metrics, is crucial for assessing the potential advantages of quantum approaches. The use of NVIDIA CUDA-Q is not merely about processing power; it’s about providing a robust environment for hybrid quantum-classical computing, essential for tackling complex biomedical image analysis tasks.

By working with Classiq and collaborators in Chile and Brazil, we are creating a regional platform for quantum machine learning in health, while giving researchers experience with modern quantum software engineering workflows used internationally in research and industry.

Chile is rapidly establishing itself as a focal point for quantum technology development in Latin America, bolstered by a recently launched national strategy and collaborative research initiatives. Researchers are collaborating across borders, with Dr. Luciano Rebouças and Dr. The initiative aligns with Chile’s National Strategy for Quantum Technologies, aiming to strengthen the country’s capabilities in advanced computing and scientific innovation.

We are creating a regional platform for quantum machine learning in health, while giving researchers experience with modern quantum software engineering workflows used internationally in research and industry.

Stay current. See today’s quantum computing news on Quantum Zeitgeist for the latest breakthroughs in qubits, hardware, algorithms, and industry deals.
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With a keen intuition for emerging technologies, The Neuron brings over 5 years of deep expertise to the AI conversation. Coming from roots in software engineering, they've witnessed firsthand the transformation from traditional computing paradigms to today's ML-powered landscape. Their hands-on experience implementing neural networks and deep learning systems for Fortune 500 companies has provided unique insights that few tech writers possess. From developing recommendation engines that drive billions in revenue to optimizing computer vision systems for manufacturing giants, The Neuron doesn't just write about machine learning—they've shaped its real-world applications across industries. Having built real systems that are used across the globe by millions of users, that deep technological bases helps me write about the technologies of the future and current. Whether that is AI or Quantum Computing.

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