Xin Wang (王鑫)

Xin Wang (王鑫)

Ph.D. candidate at Netherlands Cancer Institute.

👋 About

I am a PhD candidate in artificial intelligence for breast cancer research, working with Prof. Dr. Regina Beets-Tan, Dr. Ritse Mann, and Dr. Tao Tan as part of the Breast Imaging Group (BIG) at the Netherlands Cancer Institute (NKI).

I have recently started the Postdoc position, under Dr. Jonas Teuwen’s AI for Oncology Lab at NKI, continuing my research on the AI for breast cancer.

My research focuses on AI for breast cancer early diagnosis and future risk prediction to optimize the breast cancer screening program.

🎯 Research Interests & Expertise

🧠Deep Learning 🏥Medical Imaging 🎀Breast Cancer 📊Longitudinal Analysis 🔬Risk Prediction 📷Mammography 🤖Computer Vision 💻PyTorch ⏳Temporal Modeling 🎓Multi-task Learning

📣 News

📑 Dec, 2025
Our paper "Mammo-AGE: deep learning estimation of breast age from mammograms" was published in Nature Communications.
📑 Oct, 2025
Our paper "Predicting short-to long-term breast cancer risk from longitudinal mammographic screening history" was published in npj Breast Cancer.
🏆 May, 2025
We won the first place of "SPR Screening Mammography Recall" challenge on Kaggle! And we shared our solution on Github.
🌟 Apr, 2025
Our challenge "Universal Ultrasound Image Challenge: Multi-Organ Classification and Segmentation" (UUSIC25) were accepted at MICCAI 2025!
📑 Mar, 2025
One of our paper were accepted to IJCNN 2025.
📑 Nov, 2024
Six of our abstracts were accepted to RSNA 2024.
🏆 Oct, 2024
The same paper received the Young Scientist Award at MICCAI 2024.
🎤 Sep, 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.
📑 Jun, 2024
Three of our papers were early accepted to MICCAI 2024.
🚀 May, 2024
I officially started a new position as a Postdoctoral Fellow at NKI, working with Dr. Jonas Teuwen.
📑 Jun, 2023
Three of our papers were accepted to MICCAI 2023.
📑 Apr, 2022
Two of our abstracts were accepted to MIDL 2022.

📚 Publications

Mammo-AGE: deep learning estimation of breast age from mammograms

Xin Wang, Tao Tan, Yuan Gao, et al.
Nature Communications 2025

📑 View Paper 💻 View Code

Predicting short-to long-term breast cancer risk from longitudinal mammographic screening history

Xin Wang, Tao Tan, Yuan Gao, et al.
npj Breast Cancer 2025

📑 View Paper 💻 View Code

Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms

Xin Wang, Tao Tan, Yuan Gao, Eric Marcus, Luyi Han, Antonio Portaluri, Tianyu Zhang, Chunyao Lu, Xinglong Liang, Regina Beets-Tan, et al.
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2024

📑 View Paper 💻 View Code

Disasymnet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms Using Self-Adversarial Learning

Xin Wang, Tao Tan, Yuan Gao, Luyi Han, Tianyu Zhang, Chunyao Lu, Regina Beets-Tan, Ruisheng Su, Ritse Mann
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023

📑 View Paper 💻 View Code

2.75 D: Boosting Learning by Representing 3D Medical Imaging to 2D Features for Small Data

Xin Wang, Ruisheng Su, Weiyi Xie, Wenjin Wang, Yi Xu, Ritse Mann, Jungong Han, Tao Tan
Biomedical Signal Processing and Control 2023

📑 View Paper 💻 View Code

Artificial Intelligence in Breast Imaging

Xin Wang, Nikita Moriakov, Yuan Gao, Tianyu Zhang, Luyi Han, Ritse M. Mann
Breast Imaging: Diagnosis and Intervention 2022

📑 View Paper

You can also find more publications on Google Scholar.

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