A new Ai-based tool called Ark+ can assist chest X-ray interpretation by physicians.
RT’s Three Key Takeaways:
- Superior Diagnostic Accuracy: Ark+, a new Ai tool from Arizona State University, assists doctors when reading chest X‑rays in order to improve healthcare outcomes..
- Expert-Informed Training: Unlike typical Ai models, Ark+ was trained using over 700,000 images along with expert physician notes, significantly boosting its precision and adaptability to rare and emerging conditions.
- Open-Source and Scalable: Ark+ is freely available and designed to be shared, customized, and scaled globally, making advanced medical imaging AI accessible to clinics and hospitals everywhere, including underserved regions.
Arizona State University team of researchers has built a new Ai tool, called Ark+, to help doctors read chest X‑rays better and improve healthcare outcomes.
“Ark+ is designed to be an open, reliable and ultimately useful tool in real-world health care systems,” said Jianming Liang, an ASU professor from the College of Health Solutions, and lead author of the study published in Nature.
In a proof-of-concept study, the new Ai tool demonstrated capability in diagnosis, from common lung diseases to rare and even emerging ones like COVID-19 or avian flu.
“Our goal was to build a tool that not only performed well in our study but also can help democratize the technology to get it into the hands of potentially everyone,” said Liang. “Ultimately, we want Ai to help doctors save lives.”
Liang’s research team wanted to use Ai to help interpret the most common type of X-ray used in medicine, the chest X-ray. Chest X-rays are a big help for doctors to quickly diagnose various conditions affecting the chest, including lung problems (like pneumonia, tuberculosis or Valley fever), heart issues, broken ribs and even certain gut conditions.
But according to ASU, they can be hard to interpret, even for experienced physicians, or they may miss diagnosing rare conditions or emerging diseases, as was seen in the first year of the COVID-19 pandemic.
Ai works by training computer software on large data sets, or in the case of the Ark+ model, a total of more than 700,000 worldwide images from several publicly available X-ray datasets.
The key difference-maker for Ark+ was adding value and expertise from the human art of medicine. Liang’s team critically included all the detailed doctors’ notes compiled for every image. These expert physician notes were critical in the Ark+ learning and getting more and more accuracy as it was trained on each data set.
“Ark+ is ‘Accruing and Reusing Knowledge,’” said Liang, explaining the acronym. “That’s how we train it. And pretty much, we were thinking of a new way to train Ai models with numerous datasets via fully supervised learning.”
“Because before this, if you wanted to train a large model using multiple data sets, people usually used self-supervised learning, or you train it on the disease model, the abnormal, versus a normal x-ray.”
Other key highlights from the pilot project include:
- Foundation model for X‑rays: Ark+ is trained on many different chest X‑ray datasets from hospitals and institutions around the world. This makes it better at detecting a wide range of lung issues.
- Open and sharable: The team has released the code and pretrained models. This means other researchers can improve it or adjust it for local clinics.
- Quick learning: Ark+ can identify rare diseases even when only a few examples are available.
- Adapts to new tasks: Ark+ can be also fine‑tuned to spot new or unseen lung problems without needing full retraining.
- Resilient and fair: Ark+ works well even with uneven data and fights against biases. It can also be used in private, secure ways.
Liang also notes that the software can be adapted for any kind of medical imaging diagnosis, including CT, MRI and other imaging tools, thereby expanding its impact in the future.
Liang and his research team hopes Ark+ will become a foundation for future Ai tools in medicine, allowing better care no matter where patients live.
The Ark+ team hopes to further commercialize the software for hospitals so that researchers everywhere will use and build on their work. By sharing everything openly, they want to help doctors in all countries, even rural places without big data resources.
Source: Arizona State University
