Funding for research on AI-based point-of-care diagnostic system for cervical cancer

2023-06-26

Nina Linder, Associate Professor at the Department of Women's and Children's Health, has been approved funding from WASP-DDLS joint call for the project Predictive uncertainty estimation in deep learning-based cervical cancer screening at the point-of-care.

In December 2022, the ​SciLifeLab & Wallenberg National Program for Data-Driven Life Science (DDLS) and the Wallenberg AI, Autonomous Systems and Software Program (WASP) launched their second joint call. One of the projects that now has been approved for funding is a collaboration between Uppsala University (PI Nina Linder) and Linköping University (PI Claes Lundström).

Predictive uncertainty estimation in deep learning-based cervical cancer screening at the point-of-care

Nina Linder, Associate Professor at Department of
Women's and Children's Health

The researchers have developed an AI-based point-of-care diagnostic system with high accuracy in screening for cervical cancer in resource-limited settings. The system is a compact, portable, and easy-to-use solution that requires minimal infrastructure and connects wirelessly through mobile networks and detects atypical cervical cells in Pap smears.

However, AI systems may yield unreliable predictions when encountering data that differs from the training data. The project will explore methods to mitigate these challenges, focusing on uncertainty estimation to increase prediction robustness or detect mispredictions.

The project has significant potential by enabling more accurate, efficient, and accessible diagnostics. While focusing on resource-limited settings, the method is equally applicable in mid-to-high resource countries, potentially providing faster and more precise diagnostics. 

Additional information in the news article from SciLifeLab

Nyheter

Last modified: 2023-10-23
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