Jessica Dafflon

According to our database, Jessica Dafflon authored at least 10 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium.

Amin Adibi, Xu Cao, Zongliang Ji, Jivat Neet Kaur, Winston Chen, Elizabeth Healey, Brighton Nuwagira, Wenqian Ye, Geoffrey Woollard, Maxwell A. Xu, Hejie Cui, Johnny Xi, Trenton Chang, Vasiliki Bikia, Nicole Zhang, Ayush Noori, Yuan Xia, Md. Belal Hossain, Hanna A. Frank, Alina Peluso, Yuan Pu, Shannon Zejiang Shen, John Wu, Adibvafa Fallahpour, Sazan Mahbub, Ross Duncan, Yuwei Zhang, Yurui Cao, Zuheng Xu, Michael Craig, Rahul G. Krishnan, Rahmatollah Beheshti, James M. Rehg, Mohammad Ehsanul Karim, Megan Coffee, Leo Anthony Celi, Jason Alan Fries, Mohsen Sadatsafavi, Dennis L. Shung, Shannon K. McWeeney, Jessica Dafflon, Sarah Jabbour

CoRR, February, 2025

2024

Realistic morphology-preserving generative modelling of the brain.

Petru-Daniel Tudosiu, Walter H. L. Pinaya, Pedro Ferreira Da Costa, Jessica Dafflon, Ashay Patel, Pedro Borges, Virginia Fernandez, Mark S. Graham, Robert J. Gray, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

Nat. Mac. Intell., 2024

Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report.

Evi M. C. Huijben, Maarten L. Terpstra, Arthur Jr Galapon, Suraj Pai, Adrian Thummerer, Peter Koopmans, Manya Afonso, Maureen A. J. M. van Eijnatten, Oliver J. Gurney-Champion, Zeli Chen, Yiwen Zhang, Kaiyi Zheng, Chuanpu Li, Haowen Pang, Chuyang Ye, Runqi Wang, Tao Song, Fuxin Fan, Jingna Qiu, Yixing Huang, Juhyung Ha, Jong Sung Park, Alexandra Alain-Beaudoin, Silvain Bériault, Pengxin Yu, Hongbin Guo, Zhanyao Huang, Gengwan Li, Xueru Zhang, Yubo Fan, Han Liu, Bowen Xin, Aaron Nicolson, Lujia Zhong, Zhiwei Deng, Gustav Müller-Franzes, Firas Khader, Xia Li, Ye Zhang, Cédric Hémon, Valentin Boussot, Zhihao Zhang, Long Wang, Lu Bai, Shaobin Wang, Derk Mus, Bram Kooiman, Chelsea A. H. Sargeant, Edward G. A. Henderson, Satoshi Kondo, Satoshi Kasai, Reza Karimzadeh, Bulat Ibragimov, Thomas Helfer, Jessica Dafflon, Zijie Chen, Enpei Wang, Zoltán Perkó, Matteo Maspero

Medical Image Anal., 2024

Super-Resolution without High-Resolution Labels for Black Hole Simulations.

Thomas Helfer, Thomas D. P. Edwards, Jessica Dafflon, Kaze W. K. Wong, Matthew Lyle Olson

CoRR, 2024

Large language models surpass human experts in predicting neuroscience results.

Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun, Kevin K. Nejad, Felipe Yáñez, Bati Yilmaz, Kangjoo Lee, Alexandra O. Cohen, Valentina Borghesani, Anton Pashkov, Daniele Marinazzo, Jonathan Nicholas, Alessandro Salatiello, Ilia Sucholutsky, Pasquale Minervini, Sepehr Razavi, Roberta Rocca, Elkhan Yusifov, Tereza Okalova, Nianlong Gu, Martin Ferianc, Mikail Khona, Kaustubh R. Patil, Pui-Shee Lee, Rui Mata, Nicholas E. Myers, Jennifer K. Bizley, Sebastian Musslick, Isil Poyraz Bilgin, Guiomar Niso, Justin M. Ales, Michael Gaebler, N. Apurva Ratan Murty, Leyla Loued-Khenissi, Anna Behler, Chloe M. Hall, Jessica Dafflon, Sherry Dongqi Bao, Bradley C. Love

CoRR, 2024

Machine Learning for Health (ML4H) 2024.

Helen Zhou, Stefan Hegselmann, Elizabeth Healey, Trenton Chang, Caleb Ellington, Michael Leone, Vishwali Mhasawade, Sana Tonekaboni, Winston Chen, Hyewon Jeong, Xiaoxiao Li, Juyeon Heo, Payal Chandak, Ayush Noori, Sarah Jabbour, Jessica Dafflon, Jerry Ji, Jivat Neet Kaur, Amin Adibi, Xu Cao, Meera Krishnamoorthy, Yidi Huang, Fabian Gröger, Aishwarya Mandyam, Niloufar Saharhkhiz, Teya S. Bergamaschi, William Boag, Jeroen Berrevoets, Matthew Lee, Kyle Heuton, Peniel N. Argaw, Haoran Zhang

Proceedings of the Machine Learning for Health, 2024

2023

Generative AI for Medical Imaging: extending the MONAI Framework.

Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot, Petru-Daniel Tudosiu, Jessica Dafflon, Virginia Fernandez, Pedro Sanchez, Julia Wolleb, Pedro F. Da Costa, Ashay Patel, Hyungjin Chung, Can Zhao, Wei Peng, Zelong Liu, XueYan Mei, Oeslle Lucena, Jong Chul Ye, Sotirios A. Tsaftaris, Prerna Dogra, Andrew Feng, Marc Modat, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

CoRR, 2023

Machine Learning for Health (ML4H) 2023.

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel N. Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen

Proceedings of the Machine Learning for Health, 2023

2022

Transformer-based normative modelling for anomaly detection of early schizophrenia.

Pedro F. Da Costa, Jessica Dafflon, Sergio Leonardo Mendes, João Ricardo Sato, M. Jorge Cardoso, Robert Leech, Emily J. H. Jones, Walter Hugo Lopez Pinaya

CoRR, 2022

Brain Imaging Generation with Latent Diffusion Models.

Walter H. L. Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon, Pedro F. Da Costa, Virginia Fernandez, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

Proceedings of the Deep Generative Models - Second MICCAI Workshop, 2022