publications by categories in reversed chronological order. generated by jekyll-scholar.
2024
RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision
Fernando Pérez-Garcı́a, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel C Castro, Anton Schwaighofer, Maria Teodora Lungren, Noel Codella, Stephanie L. Hyland, Javier Alvarez-Valle, and Ozan Oktay
@article{perez2024rad,title={RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision},author={P{\'e}rez-Garc{\'\i}a, Fernando and Sharma, Harshita and Bond-Taylor, Sam and Bouzid, Kenza and Salvatelli, Valentina and Ilse, Maximilian and Bannur, Shruthi and Castro, Daniel C and Schwaighofer, Anton and Lungren, Matthew P Wetscherek, Maria Teodora and Codella, Noel and Hyland, Stephanie L. and Alvarez-Valle, Javier and Oktay, Ozan},journal={arXiv:2401.10815},year={2024},}
A comprehensive ml-based respiratory monitoring system for physiological monitoring & resource planning in the icu
Matthias Hüser, Xinrui Lyu, Martin Faltys, Alizée Pace, Marine Hoche, Stephanie Hyland, Hugo Yèche, Manuel Burger, Tobias M Merz, and Gunnar Rätsch
@article{huser2024comprehensive,title={A comprehensive ml-based respiratory monitoring system for physiological monitoring \& resource planning in the icu},author={H{\"u}ser, Matthias and Lyu, Xinrui and Faltys, Martin and Pace, Aliz{\'e}e and Hoche, Marine and Hyland, Stephanie and Y{\`e}che, Hugo and Burger, Manuel and Merz, Tobias M and R{\"a}tsch, Gunnar},journal={medRxiv},year={2024}}
Compatibility in Missing Data Handling Across the Prediction Model Pipeline: A Simulation Study
Antonia Tsvetanova, Matthew Sperrin, David Jenkins, Niels Peek, Iain Buchan, Stephanie Hyland, and Glen Martin
@incollection{tsvetanova2024compatibility,title={Compatibility in Missing Data Handling Across the Prediction Model Pipeline: A Simulation Study},author={Tsvetanova, Antonia and Sperrin, Matthew and Jenkins, David and Peek, Niels and Buchan, Iain and Hyland, Stephanie and Martin, Glen},booktitle={MEDINFO 2023—The Future Is Accessible},pages={1476--1477},year={2024},publisher={IOS Press}}
Multimodal healthcare AI: identifying and designing clinically relevant vision-language applications for radiology
Nur Yildirim, Hannah Richardson, Maria Teodora Wetscherek, Junaid Bajwa, Joseph Jacob, Mark Ames Pinnock, Stephen Harris, Daniel Coelho De Castro, Shruthi Bannur, Stephanie L Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew Lungren, Javier Alvarez-Valle, Aditya Nori, and Anja Thieme
In Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024
@inproceedings{yildirim2024multimodal,title={Multimodal healthcare AI: identifying and designing clinically relevant vision-language applications for radiology},author={Yildirim, Nur and Richardson, Hannah and Wetscherek, Maria Teodora and Bajwa, Junaid and Jacob, Joseph and Pinnock, Mark Ames and Harris, Stephen and Coelho De Castro, Daniel and Bannur, Shruthi and Hyland, Stephanie L and Ghosh, Pratik and Ranjit, Mercy and Bouzid, Kenza and Schwaighofer, Anton and Pérez-García, Fernando and Sharma, Harshita and Oktay, Ozan and Lungren, Matthew and Alvarez-Valle, Javier and Nori, Aditya and Thieme, Anja},booktitle={Proceedings of the CHI Conference on Human Factors in Computing Systems},pages={1--22},year={2024},}
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson, Fernando Pérez-García, Stephanie L. Hyland, Shruthi Bannur, Daniel C. Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, and Jacob
@article{thieme2024challenges,title={Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology},author={Thieme, Anja and Rajamohan, Abhijith and Cooper, Benjamin and Groombridge, Heather and Simister, Robert and Wong, Barney and Woznitza, Nicholas and Pinnock, Mark Ames and Wetscherek, Maria Teodora and Morrison, Cecily and Richardson, Hannah and Pérez-García, Fernando and Hyland, Stephanie L. and Bannur, Shruthi and Castro, Daniel C. and Bouzid, Kenza and Schwaighofer, Anton and Ranjit, Mercy and Sharma, Harshita and Lungren, Matthew P. and Oktay, Ozan and Alvarez-Valle, Javier and Nori, Aditya and Harris, Stephen and Jacob},journal={arXiv:2405.05299},year={2024},}
MAIRA-2: Grounded radiology report generation
Shruthi Bannur, Kenza Bouzid, Daniel C Castro, Anton Schwaighofer, Anja Thieme, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-Garcı́a, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Noel C.F. Codella, Fabian Falck, Ozan Oktay, Matthew P. Lungren, Maria Teodora Wetscherek, Javier Alvarz-Valle, and Stephanie L. Hyland
@article{bannur2024maira,title={MAIRA-2: Grounded radiology report generation},author={Bannur, Shruthi and Bouzid, Kenza and Castro, Daniel C and Schwaighofer, Anton and Thieme, Anja and Bond-Taylor, Sam and Ilse, Maximilian and P{\'e}rez-Garc{\'\i}a, Fernando and Salvatelli, Valentina and Sharma, Harshita and Meissen, Felix and Ranjit, Mercy and Srivastav, Shaury and Gong, Julia and Codella, Noel C.F. and Falck, Fabian and Oktay, Ozan and Lungren, Matthew P. and Wetscherek, Maria Teodora and Alvarz-Valle, Javier and Hyland, Stephanie L.},journal={arXiv:2406.04449},year={2024},}
An X-Ray Is Worth 15 Features: Sparse Autoencoders for Interpretable Radiology Report Generation
Ahmed Abdulaal, Hugo Fry, Nina Montaña-Brown, Ayodeji Ijishakin, Jack Gao, Stephanie Hyland, Daniel C Alexander, and Daniel C Castro
@article{abdulaal2024x,title={An X-Ray Is Worth 15 Features: Sparse Autoencoders for Interpretable Radiology Report Generation},author={Abdulaal, Ahmed and Fry, Hugo and Monta{\~n}a-Brown, Nina and Ijishakin, Ayodeji and Gao, Jack and Hyland, Stephanie and Alexander, Daniel C and Castro, Daniel C},journal={arXiv:2410.03334},year={2024},}
Medimageinsight: An open-source embedding model for general domain medical imaging
Noel C. F. Codella, Ying Jin, Shrey Jain, Yu Gu, Ho Hin Lee, Asma Ben Abacha, Alberto Santamaria-Pang, Will Guyman, Naiteek Sangani, Sheng Zhang, Hoifung Poon, Stephanie Hyland, Shruthi Bannur, Javier Alvarez-Valle, Xue Li, John Garrett, Alan McMillan, Gaurav Rajguru, Madhu Maddi, Nilesh Vijayrania, Rehaan Bhimai, Nick Mecklenburg, Rupal Jain, Daniel Holstein, Naveen Gaur, Vijay Aski, Jenq-Neng Hwang, Thomas Lin, Ivan Tarapov, Matthew Lungren, and Mu Wei
@article{codella2024medimageinsight,title={Medimageinsight: An open-source embedding model for general domain medical imaging},author={Codella, Noel C. F. and Jin, Ying and Jain, Shrey and Gu, Yu and Lee, Ho Hin and Ben Abacha, Asma and Santamaria-Pang, Alberto and Guyman, Will and Sangani, Naiteek and Zhang, Sheng and Poon, Hoifung and Hyland, Stephanie and Bannur, Shruthi and Alvarez-Valle, Javier and Li, Xue and Garrett, John and McMillan, Alan and Rajguru, Gaurav and Maddi, Madhu and Vijayrania, Nilesh and Bhimai, Rehaan and Mecklenburg, Nick and Jain, Rupal and Holstein, Daniel and Gaur, Naveen and Aski, Vijay and Hwang, Jenq-Neng and Lin, Thomas and Tarapov, Ivan and Lungren, Matthew and Wei, Mu},journal={arXiv:2410.06542},year={2024},}
PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generation
Daniel C. Castro, Aurelia Bustos, Shruthi Bannur, Stephanie L. Hyland, Kenza Bouzid, Maria Teodora Wetscherek, Maria Dolores Sánchez-Valverde, Lara Jaques-Pérez, Lourdes Pérez-Rodríguez, Kenji Takeda, José María Salinas, Javier Alvarez-Valle, Joaquín Galant Herrero, and Antonio Pertusa
@article{castro2024padchest,title={PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generation},author={Castro, Daniel C. and Bustos, Aurelia and Bannur, Shruthi and Hyland, Stephanie L. and Bouzid, Kenza and Wetscherek, Maria Teodora and Sánchez-Valverde, Maria Dolores and Jaques-Pérez, Lara and Pérez-Rodríguez, Lourdes and Takeda, Kenji and Salinas, José María and Alvarez-Valle, Javier and Galant Herrero, Joaquín and Pertusa, Antonio},journal={arXiv:2411.05085},year={2024},}
MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models
Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel C. Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Prasanna Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson, Maria Teodora Wetscherek, Stephanie L. Hyland, and Javier Alvarez-Valle
@article{sharma2024maira,title={MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models},author={Sharma, Harshita and Salvatelli, Valentina and Srivastav, Shaury and Bouzid, Kenza and Bannur, Shruthi and Castro, Daniel C. and Ilse, Maximilian and Bond-Taylor, Sam and Ranjit, Mercy Prasanna and Falck, Fabian and Pérez-García, Fernando and Schwaighofer, Anton and Richardson, Hannah and Wetscherek, Maria Teodora and Hyland, Stephanie L. and Alvarez-Valle, Javier},journal={arXiv:2411.11362},year={2024},}
2023
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Shruthi Bannur*, Stephanie Hyland*, Qianchu Liu, Fernando Pérez-García, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya Nori, Javier Alvarez-Valle, and Ozan Oktay
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
@inproceedings{bannur2023learning,title={Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing},author={Bannur, Shruthi and Hyland, Stephanie and Liu, Qianchu and Pérez-García, Fernando and Ilse, Maximilian and Castro, Daniel C. and Boecking, Benedikt and Sharma, Harshita and Bouzid, Kenza and Thieme, Anja and Schwaighofer, Anton and Wetscherek, Maria and Lungren, Matthew P. and Nori, Aditya and Alvarez-Valle, Javier and Oktay, Ozan},booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},pages={15016--15027},year={2023},}
Compositional Zero-Shot Domain Transfer with Text-to-Text Models
Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, and Stephanie L. Hyland
Transactions of the Association for Compuational Linguistics, 2023
@article{liu2023compositional,title={Compositional Zero-Shot Domain Transfer with Text-to-Text Models},author={Liu, Fangyu and Liu, Qianchu and Bannur, Shruthi and Pérez-García, Fernando and Usuyama, Naoto and Zhang, Sheng and Naumann, Tristan and Nori, Aditya and Poon, Hoifung and Alvarez-Valle, Javier and Oktay, Ozan and Hyland, Stephanie L.},journal={Transactions of the Association for Compuational Linguistics},year={2023}}
Framing machine learning opportunities for hypotension prediction in perioperative care: a socio-technical perspective: Socio-technical perspectives on hypotension prediction
Pratik Ghosh, Karen L Posner, Stephanie L Hyland, Wil Van Cleve, Melissa Bristow, Dustin R Long, Konstantina Palla, Bala Nair, Christine Fong, Ronald Pauldine, Monica S. Vavilala, and Kenton O’Hara
ACM Transactions on Computer-Human Interaction, Sep 2023
@article{ghosh2023framing,title={Framing machine learning opportunities for hypotension prediction in perioperative care: a socio-technical perspective: Socio-technical perspectives on hypotension prediction},author={Ghosh, Pratik and Posner, Karen L and Hyland, Stephanie L and Van Cleve, Wil and Bristow, Melissa and Long, Dustin R and Palla, Konstantina and Nair, Bala and Fong, Christine and Pauldine, Ronald and Vavilala, Monica S. and O'Hara, Kenton},journal={ACM Transactions on Computer-Human Interaction},volume={30},number={5},issn={1073-0516},year={2023},month=sep,articleno={79},numpages={33},publisher={Association for Computing Machinery},}
Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, and Javier Alvarez-Valle
In Conference on Empirical Methods in Natural Language Processing, Sep 2023
@inproceedings{liu2023exploring,title={Exploring the Boundaries of GPT-4 in Radiology},author={Liu, Qianchu and Hyland, Stephanie and Bannur, Shruthi and Bouzid, Kenza and Castro, Daniel C. and Wetscherek, Maria Teodora and Tinn, Robert and Sharma, Harshita and Pérez-García, Fernando and Schwaighofer, Anton and Rajpurkar, Pranav and Khanna, Sameer Tajdin and Poon, Hoifung and Usuyama, Naoto and Thieme, Anja and Nori, Aditya V. and Lungren, Matthew P. and Oktay, Ozan and Alvarez-Valle, Javier},booktitle={Conference on Empirical Methods in Natural Language Processing},year={2023},}
MAIRA-1: A specialised large multimodal model for radiology report generation
Stephanie L Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-Garcı́a, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P. Lungren, Maria Teodora Wetscherek, Ozan Oktay, and Javier Alvarez-Valle
@article{hyland2023maira,title={MAIRA-1: A specialised large multimodal model for radiology report generation},author={Hyland, Stephanie L and Bannur, Shruthi and Bouzid, Kenza and Castro, Daniel C and Ranjit, Mercy and Schwaighofer, Anton and P{\'e}rez-Garc{\'\i}a, Fernando and Salvatelli, Valentina and Srivastav, Shaury and Thieme, Anja and Codella, Noel and Lungren, Matthew P. and Wetscherek, Maria Teodora and Oktay, Ozan and Alvarez-Valle, Javier},journal={arXiv:2311.13668},year={2023},}
2022
Intraoperative prediction of postanaesthesia care unit hypotension
Konstantina Palla, Stephanie L Hyland, Karen Posner, Pratik Ghosh, Bala Nair, Melissa Bristow, Yoana Paleva, Ben Williams, Christine Fong, Wil Van Cleve, Dustin R Long, Ronald Pauldine, Kenton O’Hara, Kenji Takeda, and Monica S Vavilala
@article{palla2022intraoperative,title={Intraoperative prediction of postanaesthesia care unit hypotension},author={Palla, Konstantina and Hyland, Stephanie L and Posner, Karen and Ghosh, Pratik and Nair, Bala and Bristow, Melissa and Paleva, Yoana and Williams, Ben and Fong, Christine and Van Cleve, Wil and Long, Dustin R and Pauldine, Ronald and O'Hara, Kenton and Takeda, Kenji and Vavilala, Monica S},journal={British Journal of Anaesthesia},volume={128},number={4},pages={623--635},year={2022},publisher={Elsevier},}
Predicting the impact of treatments over time with uncertainty aware neural differential equations.
Edward De Brouwer, Javier Gonzalez, and Stephanie Hyland
In International Conference on Artificial Intelligence and Statistics, Sep 2022
@inproceedings{de2022predicting,title={Predicting the impact of treatments over time with uncertainty aware neural differential equations.},author={De Brouwer, Edward and Gonzalez, Javier and Hyland, Stephanie},booktitle={International Conference on Artificial Intelligence and Statistics},pages={4705--4722},year={2022},organization={PMLR},}
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie Hyland, Maria Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, and Ozan Oktay
In European Conference on Computer Vision, Sep 2022
@inproceedings{boecking2022making,title={Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing},author={Boecking, Benedikt and Usuyama, Naoto and Bannur, Shruthi and Castro, Daniel C. and Schwaighofer, Anton and Hyland, Stephanie and Wetscherek, Maria and Naumann, Tristan and Nori, Aditya and Alvarez-Valle, Javier and Poon, Hoifung and Oktay, Ozan},booktitle={European Conference on Computer Vision},pages={1--21},year={2022},isbn={9783031200595},issn={1611-3349},organization={Springer Nature Switzerland Cham}}
Leveraging electronic health records for data science: common pitfalls and how to avoid them
Christopher M Sauer, Li-Ching Chen, Stephanie L Hyland, Armand Girbes, Paul Elbers, and Leo A Celi
@article{sauer2022leveraging,title={Leveraging electronic health records for data science: common pitfalls and how to avoid them},author={Sauer, Christopher M and Chen, Li-Ching and Hyland, Stephanie L and Girbes, Armand and Elbers, Paul and Celi, Leo A},journal={The Lancet Digital Health},volume={4},number={12},pages={e893--e898},year={2022},publisher={Elsevier}}
Looking for Out-of-Distribution Environments in Multi-center Critical Care Data
@article{spathis2022looking,title={Looking for Out-of-Distribution Environments in Multi-center Critical Care Data},author={Spathis, Dimitris and Hyland, Stephanie L},journal={arXiv:2205.13398},year={2022},}
2021
Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit
Emma Rocheteau, Pietro Liò, and Stephanie Hyland
In Proceedings of the conference on health, inference, and learning, Sep 2021
@inproceedings{rocheteau2021temporal,title={Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit},author={Rocheteau, Emma and Li{\`o}, Pietro and Hyland, Stephanie},booktitle={Proceedings of the conference on health, inference, and learning},pages={58--68},year={2021}}
Sociodemographic and clinical features predictive of SARS-CoV-2 test positivity across healthcare visit-types
Jimmy Phuong, Stephanie L Hyland, Stephen J Mooney, Dustin R Long, Kenji Takeda, Monica S Vavilala, and Kenton O’Hara
@article{phuong2021sociodemographic,title={Sociodemographic and clinical features predictive of SARS-CoV-2 test positivity across healthcare visit-types},author={Phuong, Jimmy and Hyland, Stephanie L and Mooney, Stephen J and Long, Dustin R and Takeda, Kenji and Vavilala, Monica S and O’Hara, Kenton},journal={Plos one},volume={16},number={10},pages={e0258339},year={2021},publisher={Public Library of Science San Francisco, CA USA},}
Missing data was handled inconsistently in UK prediction models: a review of method used
Antonia Tsvetanova, Matthew Sperrin, Niels Peek, Iain Buchan, Stephanie Hyland, and Glen P Martin
@article{tsvetanova2021missing,title={Missing data was handled inconsistently in UK prediction models: a review of method used},author={Tsvetanova, Antonia and Sperrin, Matthew and Peek, Niels and Buchan, Iain and Hyland, Stephanie and Martin, Glen P},journal={Journal of Clinical Epidemiology},volume={140},pages={149--158},year={2021},publisher={Pergamon}}
2020
Early prediction of circulatory failure in the intensive care unit using machine learning
Stephanie L Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean Bodenham, Karsten Borgwardt, Gunnar Rätsch, and Tobias M. Merz
@article{hyland2020early,title={Early prediction of circulatory failure in the intensive care unit using machine learning},author={Hyland, Stephanie L and Faltys, Martin and H{\"u}ser, Matthias and Lyu, Xinrui and Gumbsch, Thomas and Esteban, Crist{\'o}bal and Bock, Christian and Horn, Max and Moor, Michael and Rieck, Bastian and Zimmermann, Marc and Bodenham, Dean and Borgwardt, Karsten and R{\"a}tsch, Gunnar and Merz, Tobias M.},journal={Nature medicine},volume={26},number={3},pages={364--373},year={2020},publisher={Nature Publishing Group US New York},}
Machine learning for health (ML4H) 2020: Advancing healthcare for all
Suproteem K Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew BA McDermott, Fabian Falck, Ioana Bica , Griffin Adams, Stephen Pfohl, and Stephanie L Hyland
@inproceedings{sarkar2020machine,title={Machine learning for health (ML4H) 2020: Advancing healthcare for all},author={Sarkar, Suproteem K and Roy, Subhrajit and Alsentzer, Emily and McDermott, Matthew BA and Falck, Fabian and Bica, Ioana and Adams, Griffin and Pfohl, Stephen and Hyland, Stephanie L},booktitle={Machine Learning for Health},pages={1--11},year={2020},organization={PMLR}}
2019
Unsupervised extraction of phenotypes from cancer clinical notes for association studies
Stefan G Stark, Stephanie L Hyland, Melanie F Pradier, Kjong Lehmann, Andreas Wicki, Fernando Perez Cruz, Julia E Vogt, and Gunnar Rätsch
@article{stark2019unsupervised,title={Unsupervised extraction of phenotypes from cancer clinical notes for association studies},author={Stark, Stefan G and Hyland, Stephanie L and Pradier, Melanie F and Lehmann, Kjong and Wicki, Andreas and Cruz, Fernando Perez and Vogt, Julia E and R{\"a}tsch, Gunnar},journal={arXiv:1904.12973},year={2019},}
A Bayesian Nonparametric Approach to Discover Clinico-Genetic Associations across Cancer Types
Melanie F Pradier, Stephanie L Hyland, Stefan G Stark, Kjong Lehmann, Julia E Vogt, Fernando Perez-Cruz, and Gunnar Rätsch
@article{pradier2019bayesian,title={A Bayesian Nonparametric Approach to Discover Clinico-Genetic Associations across Cancer Types},author={Pradier, Melanie F and Hyland, Stephanie L and Stark, Stefan G and Lehmann, Kjong and Vogt, Julia E and Perez-Cruz, Fernando and R{\"a}tsch, Gunnar},journal={bioRxiv},pages={623215},year={2019},publisher={Cold Spring Harbor Laboratory}}
An empirical study on the intrinsic privacy of SGD
@article{hyland2019empirical,title={An empirical study on the intrinsic privacy of SGD},author={Hyland, Stephanie L and Tople, Shruti},journal={arXiv:1912.02919},year={2019},}
2018
Improving clinical predictions through unsupervised time series representation learning
Xinrui Lyu, Matthias Hueser, Stephanie L Hyland, George Zerveas, and Gunnar Rätsch
@article{lyu2018improving,title={Improving clinical predictions through unsupervised time series representation learning},author={Lyu, Xinrui and Hueser, Matthias and Hyland, Stephanie L and Zerveas, George and R{\"a}tsch, Gunnar},journal={arXiv:1812.00490},year={2018}}
2017
Real-valued (medical) time series generation with recurrent conditional gans
Cristóbal Esteban, Stephanie L Hyland, and Gunnar Rätsch
@article{esteban2017real,title={Real-valued (medical) time series generation with recurrent conditional gans},author={Esteban, Crist{\'o}bal and Hyland, Stephanie L and R{\"a}tsch, Gunnar},journal={arXiv:1706.02633},year={2017},}
2016
A generative model of words and relationships from multiple sources
Stephanie L Hyland, Theofanis Karaletsos, and Gunnar Rätsch
In Association for the Advancement of Artificial Intelligence, Sep 2016
@inproceedings{hyland2016generative,title={A generative model of words and relationships from multiple sources},author={Hyland, Stephanie L and Karaletsos, Theofanis and R{\"a}tsch, Gunnar},booktitle={Association for the Advancement of Artificial Intelligence},year={2016},}
Knowledge transfer with medical language embeddings
Stephanie L Hyland, Theofanis Karaletsos, and Gunnar Rätsch
@article{hyland2016knowledge,title={Knowledge transfer with medical language embeddings},author={Hyland, Stephanie L and Karaletsos, Theofanis and R{\"a}tsch, Gunnar},journal={arXiv:1602.03551},year={2016}}
Learning Unitary Operators with Help From \mathfraku(n)
@inproceedings{hyland2016learning,title={Learning Unitary Operators with Help From \mathfrak{u}(n)},author={Hyland, Stephanie L and R{\"a}tsch, Gunnar},booktitle={AAAI 2017},year={2016},}
Neural document embeddings for intensive care patient mortality prediction
Paulina Grnarova, Florian Schmidt, Stephanie L Hyland, and Carsten Eickhoff
@article{grnarova2016neural,title={Neural document embeddings for intensive care patient mortality prediction},author={Grnarova, Paulina and Schmidt, Florian and Hyland, Stephanie L and Eickhoff, Carsten},journal={arXiv:1612.00467},year={2016},}
2015
Identification of active transcriptional regulatory elements from GRO-seq data
Charles G Danko, Stephanie L Hyland, Leighton J Core, Andre L Martins, Colin T Waters, Hyung Won Lee, Vivian G Cheung, W Lee Kraus, John T Lis, and Adam Siepel
@article{danko2015identification,title={Identification of active transcriptional regulatory elements from GRO-seq data},author={Danko, Charles G and Hyland, Stephanie L and Core, Leighton J and Martins, Andre L and Waters, Colin T and Lee, Hyung Won and Cheung, Vivian G and Kraus, W Lee and Lis, John T and Siepel, Adam},journal={Nature Methods},volume={12},number={5},pages={433--438},year={2015},publisher={Nature Publishing Group US New York},}
Large scale sentence clustering from electronic health records for genetic associations in cancer
Melanie F Pradier, Stefan Stark, Stephanie Hyland, Julia E Vogt, and Gunnar Rätsch
In Machine Learning for Computational Biology Workshop in Neural Information Processing Systems, Sep 2015
@inproceedings{pradier2015largescale,title={Large scale sentence clustering from electronic health records for genetic associations in cancer},author={Pradier, Melanie F and Stark, Stefan and Hyland, Stephanie and Vogt, Julia E and R{\"a}tsch, Gunnar},booktitle={Machine Learning for Computational Biology Workshop in Neural Information Processing Systems},year={2015},}