AI for Breast Imaging
Developing deep learning models for mammography and clinical breast imaging tasks.
Xin Wang
Postdoctoral Researcher, Netherlands Cancer Institute
AI for breast cancer screening, early detection, and future risk prediction
7+ Selected publications
4 Recent top venues
1st Kaggle challenge place
About
I am currently a postdoctoral researcher in artificial intelligence for breast cancer research at the Netherlands Cancer Institute (NKI), working with Dr. Jonas Teuwen and Dr. Ritse Mann in the AI for Oncology group.
I started my PhD in 2020 at NKI, where I work with Prof. Dr. Regina Beets-Tan, Dr. Ritse Mann, and Dr. Tao Tan as part of the Breast Imaging Group (BIG).
My research focuses on AI for breast cancer early detection and future risk prediction to optimize breast cancer screening.
Research Focus
Early Detection
Building systems for early breast cancer detection from real-world screening data.
Risk Prediction
Modeling future breast cancer risk from longitudinal mammographic histories.
Publications
View all publicationsYou can also find more publications on Google Scholar.
Review Service
- MICCAI 2024 2025
- MICCAI Workshop: Deep-Brea3th 2024
- Computational and Structural Biotechnology Journal
- Medical Physics
- BMC Cancer
- Scientific Data
- npj Digital Medicine
- Archives of Computational Methods in Engineering
- Artificial Intelligence Review
- AI Validation Group of the RSNA challenges: Lumbar Spine Degenerative Classification AI Challenge (2024), Abdominal Trauma Detection AI Challenge (2023), Screening Mammography Breast Cancer Detection AI Challenge (2023)
News
Our paper "Incorporating global-local tissue changes to predict future breast cancer from longitudinal screening mammograms" was published in Medical Image Analysis.
Our paper "Mammo-AGE: deep learning estimation of breast age from mammograms" was published in Nature Communications.
Our paper "Predicting short-to long-term breast cancer risk from longitudinal mammographic screening history" was published in npj Breast Cancer.
We won the first place of "SPR Screening Mammography Recall" challenge on Kaggle! And we shared our solution on Github.
Our challenge "Universal Ultrasound Image Challenge: Multi-Organ Classification and Segmentation" (UUSIC25) were accepted at MICCAI 2025!
One of our paper were accepted to IJCNN 2025.
Six of our abstracts were accepted to RSNA 2024.
The same paper received the Young Scientist Award at MICCAI 2024.
Our breast cancer risk prediction paper, "Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms", was selected for oral presentation at MICCAI 2024.
Three of our papers were early accepted to MICCAI 2024.
I officially started a new position as a Postdoctoral Fellow at NKI, working with Dr. Jonas Teuwen.
Three of our papers were accepted to MICCAI 2023.
Two of our abstracts were accepted to MIDL 2022.
Achievements
Kaggle 1st Place
SPR Screening Mammography Recall challenge, May 2025
Young Scientist Award
MICCAI 2024
Academic Service
MICCAI reviewer and RSNA AI validation group