AI Research

UCLA AI detects dangerous errors in AI for digital pathology

Published

4 weeks ago

August 21, 2025

FINDINGS

A team led by researchers at the California NanoSystems Institute at UCLA created an artificial intelligence-based tool to assist an emerging technology for digital pathology. AI systems are currently being trained to paint microscopic images of transparent tissue samples that physicians examine for diagnosis, in a process called virtual staining. In the study, the researchers report on an AI of their own to detect potentially life-threatening errors, called realistic hallucinations, that occasionally come from virtual staining AI models — and autonomously detect those errors without using slides stained correctly by human experts.

This AI technique is called autonomous quality and hallucination assessment tool for virtually stained tissue images, or AQuA. With a set of virtually stained images of human kidney and lung samples, the new tool had 99.8% accuracy telling the difference between images with errors and those without. AQuA detected realistic hallucinations that were missed by board-certified pathologists who reviewed the same stained images. In other experiments, the AI detected hallucinations of different types than included in the data used to train it, as well as errors in images stained by human lab technicians.

Ozcan Lab/UCLA

A diagram summarizes the machine learning process behind a UCLA-developed AI system for finding potentially dangerous errors in virtual staining.

BACKGROUND

For pathologists to identify cancer and other diseases based on biopsies, the nearly transparent samples of thin tissue sections must be stained with special dyes, a practice applied for over a century in medicine. In the years ahead, generative AI systems are expected to emulate the chemical staining process in a way that’s faster, cheaper and more efficient.

Labs can take hours, and sometimes up to a day, to stain a sample; AI algorithms could virtually stain a microscopic image in less than a minute. AI results would also be more consistent than the work of human experts, which can vary by country and region, between labs, and even among the work of a single technician. Staining in labs is labor-intensive, uses up expensive chemicals and produces millions of gallons of toxic wastewater each year, so virtual staining could also save on costs while being carbon neutral. And virtual staining doesn’t deplete tissue samples, offering the potential to reduce or even eliminate repeat biopsies.

However, generative AI carries the risk of hallucinations. In the same way that a chatbot sometimes states false information as fact, a virtual staining AI might occasionally hallucinate structures that aren’t present in the actual sample. Realistic hallucinations can be so convincing that they fool pathologists to believe that the tissue sample is stained very well. In reality, such a hallucination shows tissue structures that belong to an entirely imaginary patient.

With detecting diseases such as cancer or transplant rejection, the stakes are monumental. False positives can lead to unnecessary treatments, while unnoticed tumors or organ rejection can lead to catastrophic health problems and even death. Because pathology results help guide choices for therapy, evaluation errors due to hallucinations could sabotage a patient’s treatment plan.

METHOD

AQuA is a machine learning system designed to resemble the network of neurons in the human brain. Starting with a set of unstained microscopic images of human tissue samples, the AQuA model assessed changes in key microscopic measurements as the images cycled back and forth between a virtual staining algorithm and an algorithm that reverses the process to digitally generate unstained images. In the process, AQuA “learned” to connect virtual staining to the original microscopic image of the unprocessed tissue sample and tell the difference between correct and hallucinated images.

IMPACT

When virtual staining AI models make their way to use in the clinic, the UCLA researchers’ system could serve as an essential gatekeeper ensuring that pathologists make potentially life-and-death judgments based on accurate pathology images. AQuA might also be extended to test and periodically certify virtual staining models as part of a digital pathology workflow. Another crucial application could be protecting against cyberattacks that purposely add errors to virtually stained images in order to inject chaos into a health system.

AUTHORS

The study’s corresponding author is Aydogan Ozcan, the Volgenau Professor of Engineering Innovation and professor of electrical and computer engineering and of bioengineering in the UCLA Samueli School of Engineering, the CNSI’s associate director for entrepreneurship, industry and academic exchange, and a professor with the Howard Hughes Medical Institute. The first author is Luzhe Huang, who earned a Ph.D. from UCLA in 2024. Other co-authors are Yuzhu Li and Nir Pillar, both of UCLA; Tal Keidar Haran of Hadassah Hebrew University Medical Center in Israel; and William Dean Wallace of USC.

DISCLOSURES

The technology described in this study is covered by a patent application filed by the UCLA Technology Development Group on behalf of the Regents of the University of California, with co-authors Ozcan, Huang and Pillar listed as inventors.

JOURNAL

The study was published in the journal Nature Biomedical Engineering.

DOI: 10.1038/s41551-025-01421-9

FUNDING

The study was supported by UCLA Samueli’s V. M. Watanabe Excellence in Research Award.

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Related Topics:bioengineering Engineering nanotechnology Research Science

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AI Research

‘AI Learning Day’ spotlights smart campus and ecosystem co-creation

Published

1 hour ago

September 17, 2025

The Editors

When artificial intelligence (AI) can help you retrieve literature, support your research, and even act as a “super assistant”, university education is undergoing a profound transformation.

On 9 September, XJTLU’s Centre for Knowledge and Information (CKI) hosted its third AI Learning Day, themed “AI-Empowered, Ecosystem-Co-created”. The event showcased the latest milestones of the University’s “Education + AI” strategy and offered in-depth discussions on the role of AI in higher education.

In her opening remarks, Professor Qiuling Chao, Vice President of XJTLU, said: “AI offers us an opportunity to rethink education, helping us create a learning environment that is fairer, more efficient and more personalised. I hope today’s event will inspire everyone to explore how AI technologies can be applied in your own practice.”

Professor Qiuling Chao

In his keynote speech, Professor Youmin Xi, Executive President of XJTLU, elaborated on the University’s vision for future universities. He stressed that future universities would evolve into human-AI symbiotic ecosystems, where learning would be centred on project-based co-creation and human-AI collaboration. The role of educators, he noted, would shift from transmitters of knowledge to mentors for both learning and life.

Professor Youmin Xi

At the event, Professor Xi’s digital twin, created by the XJTLU Virtual Engineering Centre in collaboration with the team led by Qilei Sun from the Academy of Artificial Intelligence, delivered Teachers’ Day greetings to all staff.

(Teachers’ Day message from President Xi’s digital twin)

“Education + AI” in diverse scenarios

This event also highlighted four case studies from different areas of the University. Dr Ling Xia from the Global Cultures and Languages Hub suggested that in the AI era, curricula should undergo de-skilling (assigning repetitive tasks to AI), re-skilling, and up-skilling, thereby enabling students to focus on in-depth learning in critical thinking and research methodologies.

Dr Xiangyun Lu from International Business School Suzhou (IBSS) demonstrated how AI teaching assistants and the University’s Junmou AI platform can offer students a customised and highly interactive learning experience, particularly for those facing challenges such as information overload and language barriers.

Dr Juan Li from the School of Science shared the concept of the “AI amplifier” for research. She explained that the “double amplifier” effect works in two stages: AI first amplifies students’ efficiency by automating tasks like literature searches and coding. These empowered students then become the second amplifier, freeing mentors from routine work so they can focus on high-level strategy. This human-AI partnership allows a small research team to achieve the output of a much larger one.

Jing Wang, Deputy Director of the XJTLU Learning Mall, showed how AI agents are already being used to support scheduling, meeting bookings, news updates and other administrative and learning tasks. She also announced that from this semester, all students would have access to the XIPU AI Agent platform.

Students and teachers are having a discussion at one of the booths

AI education system co-created by staff and students

The event’s AI interactive zone also drew significant attention from students and staff. From the Junmou AI platform to the E

-Support chatbot, and from AI-assisted creative design to 3D printing, 10 exhibition booths demonstrated the integration of AI across campus life.

These innovative applications sparked lively discussions and thoughtful reflections among participants. In an interview, Thomas Durham from IBSS noted that, although he had rarely used AI before, the event was highly inspiring and motivated him to explore its use in both professional and personal life. He also shared his perspective on AI’s role in learning, stating: “My expectation for the future of AI in education is that it should help students think critically. My worry is that AI’s convenience and efficiency might make students’ understanding too superficial, since AI does much of the hard work for them. Hopefully, critical thinking will still be preserved.”

Year One student Zifei Xu was particularly inspired by the interdisciplinary collaboration on display at the event, remarking that it offered her a glimpse of a more holistic and future-focused education.

Dr Xin Bi, XJTLU’s Chief Officer of Data and Director of the CKI, noted that, supported by robust digital infrastructure such as the Junmou AI platform, more than 26,000 students and 2,400 staff are already using the University’s AI platforms. XJTLU’s digital transformation is advancing from informatisation and digitisation towards intelligentisation, with AI expected to empower teaching, research and administration, and to help staff and students leap from knowledge to wisdom.

Dr Xin Bi

“Looking ahead, we will continue to advance the deep integration of AI in education, research, administration and services, building a data-driven intelligent operations centre and fostering a sustainable AI learning ecosystem,” said Dr Xin Bi.

By Qinru Liu

Edited by Patricia Pieterse

Translated by Xiangyin Han

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AI Research

Vietnam plans to introduce Law on Artificial Intelligence

Published

1 hour ago

September 17, 2025

Vietnam Investment Review - VIR

This information was announced by Minister of Science and Technology Nguyen Manh Hung at a conference organised by the Ho Chi Minh National Academy of Politics in coordination with the Ministry of Public Security, the Ministry of National Defense, and the Central Theoretical Council in Hanoi on September 15.

Minister of Science and Technology Nguyen Manh Hung. Photo: MST

At the event, experts, businesses, and managers shared their ideas in two discussion sessions. The first session focused on AI power, risks and control, analysing both positive and negative aspects, affirming the need to exploit potential and control ethics, safety, security, and social risks.

In the second session, they discussed national AI development strategy, from vision to actions, a specific roadmap to make AI a pillar in Vietnam’s socioeconomic development.

They agreed that for AI to truly become a driving force for development, Vietnam needs a comprehensive strategy: data infrastructure, high-quality human resources, a complete legal framework, and a dynamic innovation ecosystem. More importantly, AI must be oriented to serve people, protect human rights, and strengthen national security in the digital age.

According to Minister Hung, Vietnam issued its first AI Strategy in 2021, but AI is a rapidly changing field, so the strategy needed to be updated.

By the end of this year, the country will have an updated version of the National AI Strategy and the AI Law. This is not only a legal framework, but also a declaration of national vision. AI must become the country’s intellectual infrastructure, serving the people, developing sustainably, and enhancing national competitiveness.

Regarding open AI technology, Hung emphasised that Vietnam is committed to developing and mastering digital technology, including AI, based on open standards and open-source code. This is also Vietnam’s strategy to develop and master Vietnamese technology, implementing the “Make in Vietnam” programme.

Vietnam plans to introduce Law on Artificial Intelligence

Experts, businesses, and managers share their ideas at the conference. Photo: MST

Regarding creating a domestic AI market, he said that without applications, there will be no market. Without a market, Vietnamese AI enterprises will remain small. Therefore, promoting AI applications in enterprises, in state agencies and key areas is the fastest way to develop AI and create Vietnamese AI enterprises.

“The government will spend more on AI, the Natif Technology Innovation Fund of the Ministry of Science and Technology will spend at least 40 per cent to support AI applications, issue vouchers for small and medium-sized enterprises using Vietnamese AI. The domestic market is the cradle to create Vietnamese AI enterprises,” he noted.

In terms of policy and institutions, he added that Vietnam will issue a national AI ethics code that is in line with international standards but suitable for Vietnamese practice, and at the same time develop an AI Law and an AI strategy with core principles including risk-based management, transparency and accountability, putting people at the center, encouraging domestic AI development, AI autonomy, using AI as a driving force for rapid and sustainable growth, and protecting digital sovereignty based on three pillars: data, infrastructure, and AI technology.

According to the MST, Vietnam’s AI development will have to be based on four important pillars: transparent institutions, modern infrastructure, high-quality human resources, and humane culture.

Time for Vietnam to make breakthroughs

Speaking at the workshop, Luong Tam Quang, Minister of Public Security, said that AI is considered one of the key technologies, a factor that can lead to changes in the global order.

Luong Tam Quang, Minister of Public Security. Photo: MST

He added that with the ability to promote economic growth, optimise production, improve healthcare, innovate education, and enhance social governance capacity, AI helps countries save costs, increase efficiency, and expand knowledge. It is also a resource, and a driving force to affirm the country’s position in the digital age.

According to Minister Quang, Vietnam’s potential for AI development is huge, and is expected to contribute about $79.3 billion, equivalent to 12 per cent of Vietnam’s GDP in 2030 if widely applied. Under the leadership of the Party, legal regulations for the development of AI have gradually taken shape.

Prof. Dr. Nguyen Xuan Thang, director of the Ho Chi Minh National Academy of Politics, and chairman of the Central Theoretical Council, said that AI is becoming an indispensable part in the process of establishing a new growth model and the operation, governance, and management of the country’s society and economy.

Prof. Dr. Nguyen Xuan Thang, director of the Ho Chi Minh National Academy of Politics, and chairman of the Central Theoretical Council. Photo: MST

However, to turn potential into reality, it requires the support of the entire ecosystem, from national strategies and policies to implementation in businesses, institutes, schools, and the community.

“AI cannot develop sustainably without responsibility, ethics, and a clear humanistic orientation. Technology is the tool, while humans are the goal and the deciding factor, because even if it possesses unlimited power as many people believe, AI is still a product created by humans,” Thang emphasised.

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