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Champaign, IL
A new artificial intelligence (AI) model is developed that accurately identifies tumors and diseases in medical images by explaining each diagnosis with a visual map.
Sourya Sengupta, a graduate student at Beckman Institute for Advanced Science and Technology in the US and the lead author of the study, emphasized the significance of this development, stating, “The idea is to help catch cancer and disease in its earliest stages — like an X on a map — and understand how the decision was made. Our model will help streamline that process and make it easier on doctors and patients alike,” said Sengupta.
The unique transparency of the model, described in the journal IEEE Transactions on Medical Imaging, allows doctors to easily follow its line of reasoning, double-check for accuracy, and explain the results to patients, the researchers said.
Sengupta is a graduate student at University of Illinois at Urbana Champaign. He completed MS (by Research) from University of Waterloo and B.E. from Jadavpur University, India. His current research interest includes Medical Imaging and deep learning.
The new AI model’s transparency is expected to have a significant impact on the process of decoding medical images, particularly in regions with a scarcity of doctors and long patient queues. Sengupta highlighted the potential of AI in such scenarios, stating, “When time and talent are in high demand, automated medical image screening can be deployed as an assistive tool – in no way replacing the skill and expertise of doctors.”
This innovative approach to disease diagnosis is expected to have a profound impact on the early detection and understanding of various medical conditions, marking a significant milestone in the intersection of AI and healthcare.
