Cascaded transform space watermarking based on analysis of local entropy variation. - Shekoofeh Azizi; Shadrokh Samavi; Majid Mohrekesh; Shahram Shirani (ICME Workshops, 2013)

Stereo image watermarking method based on binocular just noticeable difference. - Sepideh Akhavan Bitaghsir; Nader Karimi; Shekoofeh Azizi; Shadrokh Samavi (ISCISC, 2014)

Ultrasound-Based Detection of Prostate Cancer Using Automatic Feature Selection with Deep Belief Networks. - Shekoofeh Azizi; Farhad Imani; Bo Zhuang; Amir M. Tahmasebi; Jin Tae Kwak; Sheng Xu 001; Nishant Uniyal; Baris Turkbey; Peter L. Choyke; Peter A. Pinto; Bradford J. Wood; Mehdi Moradi; et al. (MICCAI (2), 2015)

Classifying Cancer Grades Using Temporal Ultrasound for Transrectal Prostate Biopsy. - Shekoofeh Azizi; Farhad Imani; Jin Tae Kwak; Amir M. Tahmasebi; Sheng Xu 001; Pingkun Yan; Jochen Kruecker; Baris Turkbey; Peter L. Choyke; Peter A. Pinto; Bradford J. Wood; Parvin Mousavi; et al. (MICCAI (1), 2016)

Detection of prostate cancer using temporal sequences of ultrasound data: a large clinical feasibility study. - Shekoofeh Azizi; Farhad Imani; Sahar Ghavidel; Amir M. Tahmasebi; Jin Tae Kwak; Sheng Xu 001; Baris Turkbey; Peter L. Choyke; Peter A. Pinto; Bradford J. Wood; Parvin Mousavi; Purang Abolmaesumi (Int. J. Comput. Assist. Radiol. Surg., 2016)

Detection and grading of prostate cancer using temporal enhanced ultrasound: combining deep neural networks and tissue mimicking simulations. - Shekoofeh Azizi; Sharareh Bayat; Pingkun Yan; Amir M. Tahmasebi; Guy Nir; Jin Tae Kwak; Sheng Xu 001; Storey Wilson; Kenneth A. Iczkowski; M. Scott Lucia; Larry Goldenberg; Septimiu E. Salcudean; et al. (Int. J. Comput. Assist. Radiol. Surg., 2017)

Transfer learning from RF to B-mode temporal enhanced ultrasound features for prostate cancer detection. - Shekoofeh Azizi; Parvin Mousavi; Pingkun Yan; Amir M. Tahmasebi; Jin Tae Kwak; Sheng Xu 001; Baris Turkbey; Peter L. Choyke; Peter A. Pinto; Bradford J. Wood; Purang Abolmaesumi (Int. J. Comput. Assist. Radiol. Surg., 2017)

Learning from Noisy Label Statistics: Detecting High Grade Prostate Cancer in Ultrasound Guided Biopsy. - Shekoofeh Azizi; Pingkun Yan; Amir M. Tahmasebi; Peter A. Pinto; Bradford J. Wood; Jin Tae Kwak; Sheng Xu 001; Baris Turkbey; Peter L. Choyke; Parvin Mousavi; Purang Abolmaesumi (MICCAI (4), 2018)

3D tissue mimicking biophantoms for ultrasound imaging: bioprinting and image analysis. - Shekoofeh Azizi; Sharareh Bayat; Ajay Rajaram; Emran Mohammad Abu Anas; Tamer Mohamed; Konrad Walus; Purang Abolmaesumi; Parvin Mousavi (Image-Guided Procedures, 2018)

Toward a real-time system for temporal enhanced ultrasound-guided prostate biopsy. - Shekoofeh Azizi; Nathan Van Woudenberg; Samira Sojoudi; Ming Li 052; Sheng Xu 001; Emran Mohammad Abu Anas; Pingkun Yan; Amir M. Tahmasebi; Jin Tae Kwak; Baris Turkbey; Peter L. Choyke; Peter A. Pinto; et al. (Int. J. Comput. Assist. Radiol. Surg., 2018)

Hierarchical watermarking framework based on analysis of local complexity variations. - Majid Mohrekesh; Shekoofeh Azizi; Shahram Shirani; Nader Karimi; Shadrokh Samavi (Multim. Tools Appl., 2018)

Deep Recurrent Neural Networks for Prostate Cancer Detection: Analysis of Temporal Enhanced Ultrasound. - Shekoofeh Azizi; Sharareh Bayat; Pingkun Yan; Amir Tahmasebi; Jin Tae Kwak; Sheng Xu 001; Baris Turkbey; Peter L. Choyke; Peter A. Pinto; Bradford J. Wood; Parvin Mousavi; Purang Abolmaesumi (IEEE Trans. Medical Imaging, 2018)

A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations. - Saeid Asgari Taghanaki; Kumar Abhishek 001; Shekoofeh Azizi; Ghassan Hamarneh (CVPR, 2019)

Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier. - Blake Pyman; Alireza Sedghi; Shekoofeh Azizi; Kathrin Tyryshkin; Neil Renwick; Parvin Mousavi (PSB, 2019)

Deep neural maps for unsupervised visualization of high-grade cancer in prostate biopsies. - Alireza Sedghi; Mehran Pesteie; Golara Javadi; Shekoofeh Azizi; Pingkun Yan; Jin Tae Kwak; Sheng Xu 001; Baris Turkbey; Peter L. Choyke; Peter A. Pinto; Bradford J. Wood; Robert Rohling; et al. (Int. J. Comput. Assist. Radiol. Surg., 2019)

Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting. - Zili Yi; Qiang Tang 002; Shekoofeh Azizi; Daesik Jang; Zhan Xu (CVPR, 2020)

Big Self-Supervised Models Advance Medical Image Classification. - Shekoofeh Azizi; Basil Mustafa; Fiona Ryan; Zachary Beaver; Jan Freyberg; Jonathan Deaton; Aaron Loh; Alan Karthikesalingam; Simon Kornblith; Ting Chen 007; Vivek Natarajan; Mohammad Norouzi 002 (ICCV, 2021)

Deep Bregman Divergence for Contrastive Learning of Visual Representations. - Mina Rezaei; Farzin Soleymani; Bernd Bischl; Shekoofeh Azizi (CoRR, 2021)

IJCARS - IPCAI 2022 special issue: 13th international conference on information processing in computer-assisted interventions 2022 - part 1. - Shekoofeh Azizi; Alexander Seitel (Int. J. Comput. Assist. Radiol. Surg., 2022)

Robust and Efficient Medical Imaging with Self-Supervision. - Shekoofeh Azizi; Laura Culp; Jan Freyberg; Basil Mustafa; Sebastien Baur; Simon Kornblith; Ting Chen 007; Patricia MacWilliams; S. Sara Mahdavi; Ellery Wulczyn; Boris Babenko; Megan Wilson; et al. (CoRR, 2022)

Joint Debiased Representation and Image Clustering Learning with Self-Supervision. - Shunjie-Fabian Zheng; JaeEun Nam; Emilio Dorigatti; Bernd Bischl; Shekoofeh Azizi; Mina Rezaei (CoRR, 2022)

Large Language Models Encode Clinical Knowledge. - Karan Singhal; Shekoofeh Azizi; Tao Tu 001; S. Sara Mahdavi; Jason Wei; Hyung Won Chung; Nathan Scales; Ajay Kumar Tanwani; Heather Cole-Lewis; Stephen Pfohl; Perry Payne; Martin Seneviratne; et al. (CoRR, 2022)

Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions. - Abhijit Guha Roy; Jie Ren 006; Shekoofeh Azizi; Aaron Loh; Vivek Natarajan; Basil Mustafa; Nick Pawlowski; Jan Freyberg; Yuan Liu; Zachary Beaver; Nam Vo; Peggy Bui; et al. (Medical Image Anal., 2022)

Generative models improve fairness of medical classifiers under distribution shifts. - Ira Ktena; Olivia Wiles; Isabela Albuquerque; Sylvestre-Alvise Rebuffi; Ryutaro Tanno; Abhijit Guha Roy; Shekoofeh Azizi; Danielle Belgrave; Pushmeet Kohli; Alan Karthikesalingam; A. Taylan Cemgil; Sven Gowal (CoRR, 2023)

Towards Expert-Level Medical Question Answering with Large Language Models. - Karan Singhal; Tao Tu 001; Juraj Gottweis; Rory Sayres; Ellery Wulczyn; Le Hou; Kevin Clark; Stephen Pfohl; Heather Cole-Lewis; Darlene Neal; Mike Schaekermann; Amy Wang; et al. (CoRR, 2023)

Towards Generalist Biomedical AI. - Tao Tu 001; Shekoofeh Azizi; Danny Driess; Mike Schaekermann; Mohamed Amin; Pi-Chuan Chang; Andrew Carroll; Chuck Lau; Ryutaro Tanno; Ira Ktena; Basil Mustafa; Aakanksha Chowdhery; et al. (CoRR, 2023)

Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation. - Ryutaro Tanno; David G. T. Barrett; Andrew Sellergren; Sumedh Ghaisas; Sumanth Dathathri; Abigail See; Johannes Welbl; Karan Singhal; Shekoofeh Azizi; Tao Tu 001; Mike Schaekermann; Rhys May; et al. (CoRR, 2023)

Towards Accurate Differential Diagnosis with Large Language Models. - Daniel McDuff; Mike Schaekermann; Tao Tu 001; Anil Palepu; Amy Wang; Jake Garrison; Karan Singhal; Yash Sharma; Shekoofeh Azizi; Kavita Kulkarni; Le Hou; Yong Cheng; et al. (CoRR, 2023)

Synthetic Data from Diffusion Models Improves ImageNet Classification. - Shekoofeh Azizi; Simon Kornblith; Chitwan Saharia; Mohammad Norouzi 002; David J. Fleet (Trans. Mach. Learn. Res., 2023)

Deep Bregman divergence for self-supervised representations learning. - Mina Rezaei; Farzin Soleymani; Bernd Bischl; Shekoofeh Azizi (Comput. Vis. Image Underst., 2023)

Towards Conversational Diagnostic AI. - Tao Tu 001; Anil Palepu; Mike Schaekermann; Khaled Saab 003; Jan Freyberg; Ryutaro Tanno; Amy Wang; Brenna Li; Mohamed Amin; Nenad Tomasev; Shekoofeh Azizi; Karan Singhal; et al. (CoRR, 2024)

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models. - Stephen R. Pfohl; Heather Cole-Lewis; Rory Sayres; Darlene Neal; Mercy Nyamewaa Asiedu; Awa Dieng; Nenad Tomasev; Qazi Mamunur Rashid; Shekoofeh Azizi; Negar Rostamzadeh; Liam G. McCoy; Leo Anthony Celi; et al. (CoRR, 2024)

Capabilities of Gemini Models in Medicine. - Khaled Saab 003; Tao Tu 001; Wei-Hung Weng; Ryutaro Tanno; David Stutz; Ellery Wulczyn; Fan Zhang; Tim Strother; Chunjong Park; Elahe Vedadi; Juanma Zambrano Chaves; Szu-Yeu Hu; et al. (CoRR, 2024)

Advancing Multimodal Medical Capabilities of Gemini. - Lin Yang; Shawn Xu; Andrew Sellergren; Timo Kohlberger; Yuchen Zhou; Ira Ktena; Atilla P. Kiraly; Faruk Ahmed; Farhad Hormozdiari; Tiam Jaroensri; Eric Wang; Ellery Wulczyn; et al. (CoRR, 2024)

Tx-LLM: A Large Language Model for Therapeutics. - Juan Manuel Zambrano Chaves; Eric Wang; Tao Tu 001; Eeshit Dhaval Vaishnav; Byron Lee; S. Sara Mahdavi; Christopher Semturs; David J. Fleet; Vivek Natarajan; Shekoofeh Azizi (CoRR, 2024)

Decoding Visual Experience and Mapping Semantics through Whole-Brain Analysis Using fMRI Foundation Models. - Yanchen Wang; Adam Turnbull; Tiange Xiang; Yunlong Xu 001; Sa Zhou; Adnan Masoud; Shekoofeh Azizi; Feng Vankee Lin; Ehsan Adeli 001 (CoRR, 2024)

Health AI Developer Foundations. - Atilla P. Kiraly; Sebastien Baur; Kenneth Philbrick; Fereshteh Mahvar; Liron Yatziv; Tiffany Chen; Bram Sterling; Nick George; Fayaz Jamil; Jing Tang; Kai Bailey; Faruk Ahmed; et al. (CoRR, 2024)

TxGemma: Efficient and Agentic LLMs for Therapeutics. - Eric Wang; Samuel Schmidgall; Paul F. Jaeger; Fan Zhang; Rory Pilgrim; Yossi Matias; Joelle K. Barral; David J. Fleet; Shekoofeh Azizi (CoRR, 2025)

MedGemma Technical Report. - Andrew Sellergren; Sahar Kazemzadeh; Tiam Jaroensri; Atilla P. Kiraly; Madeleine Traverse; Timo Kohlberger; Shawn Xu; Fayaz Jamil; Cían Hughes; Charles Lau; Justin Chen; Fereshteh Mahvar; et al. (CoRR, 2025)