AI TURNS COMPUTERS INTO VIRTUAL PATHOLOGISTS
Our healthcare system is under enormous pressure. There is a looming shortage of healthcare providers while people, on average, live longer and need more care. For instance, there is a worldwide shortage of pathologists, medical specialists who examine tissue from patients to make a diagnosis. To reduce pressure on current specialists and guarantee the quality of care for the future, healthcare innovations are urgently needed.
The work of the Computational Pathology Group may provide the answer. Over the past decade, the team has developed several software models based on artificial intelligence (AI) that can help pathologists diagnose diseases such as cancer. By training algorithms with large digital datasets, consisting of images of often thousands of patients, the group has designed innovative AI models. These models can accurately analyse digitised images of diseased tissue and make diagnoses and even predictions based on them.
To guarantee the quality of healthcare for the future, innovations are urgently needed
The group was one of the first in the world to show that AI can match and even exceed the performance of human experts in diagnostic tasks, including assessing the severity of breast and prostate cancer. A follow-up study researched how this affected the daily work of a pathologist. Pathologists performed their tasks without and then with AI modelling. It was found that working together with AI resulted in more consistent and accurate assessments. Remarkably, even a trainee pathologist working in a country with little economic clout suddenly scored as well as a highly specialised pathologist in the Netherlands when aided by AI.
Meanwhile, the researchers are ready for their next ambitious step: they want to develop one of the world’s first virtual pathologists. This new AI model, which they call ANTONI, will be able to independently make clinical diagnoses for various tissue types including breast, prostate and colon cancer. What makes ANTONI special is that it will offer a form of ‘explainable AI’, meaning that medical specialists can ask about the reasoning behind the results to support diagnoses. This feature could boost clinicians’ confidence and open the door to broad applications of AI within healthcare.
AI is not an end in itself, but a means to improve patient care
This interdisciplinary research group brings together expertise in computer science, pathology, biomedical and software engineering, applied mathematics and computer vision. Together, they are a strong example of team science, with researchers with unique skills effectively working together to achieve something greater than the sum of its parts. Also highly admirable is their commitment to open science. Unlike many commercial AI developers, the group make all their models, codes and data freely available, allowing other scientists to build on their work.
The Computational Pathology Group focuses on both fundamental questions about artificial intelligence and its clinical application. All their work takes place within hospital walls and they involve a wide range of stakeholders, ranging from patients to clinicians, in their research. They do this based on the belief that AI is not an end in itself, but rather a means to improve patient care and make diagnostics as effective and efficient as possible. In short, this team’s research not only contributes to long-term scientific progress, but also directly benefits patients and pathologists worldwide.
