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ORCIDStephanie L. Hyland
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2020 – today
- 2024
[c15]Shaury Srivastav, Mercy Ranjit, Fernando Pérez-García, Kenza Bouzid, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Harshita Sharma, Maximilian Ilse, Valentina Salvatelli, Sam Bond-Taylor, Fabian Falck, Anja Thieme, Hannah Richardson, Matthew P. Lungren, Stephanie L. Hyland, Javier Alvarez-Valle:
MAIRA at RRG24: A specialised large multimodal model for radiology report generation. BioNLP@ACL 2024: 597-602- [c14]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 P. Lungren, Javier Alvarez-Valle, Aditya V. Nori, Anja Thieme:
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. CHI 2024: 444:1-444:22 - [i24]Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Matthew P. Lungren, Maria Wetscherek, Noel Codella, Stephanie L. Hyland, Javier Alvarez-Valle, Ozan Oktay:
RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision. CoRR abs/2401.10815 (2024) - [i23]Nur Yildirim, Hannah Richardson, Maria T. A. Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A. 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 P. Lungren, Javier Alvarez-Valle, Aditya V. Nori, Anja Thieme:
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. CoRR abs/2402.14252 (2024) - [i22]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 V. Nori, Stephen Harris, Joseph Jacob:
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology. CoRR abs/2405.05299 (2024) - [i21]Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P. Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie L. Hyland:
MAIRA-2: Grounded Radiology Report Generation. CoRR abs/2406.04449 (2024) - 2023
- [j2]Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland:
Compositional Zero-Shot Domain Transfer with Text-to-Text Models. Trans. Assoc. Comput. Linguistics 11: 1097-1113 (2023) - [j1]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, Kenton O'Hara:
Framing Machine Learning Opportunities for Hypotension Prediction in Perioperative Care: A Socio-technical Perspective: Socio-technical perspectives on hypotension prediction. ACM Trans. Comput. Hum. Interact. 30(5): 79:1-79:33 (2023) - [c13]Shruthi Bannur, Stephanie L. 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 V. Nori, Javier Alvarez-Valle, Ozan Oktay:
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. CVPR 2023: 15016-15027 - [c12]Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria 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, Javier Alvarez-Valle:
Exploring the Boundaries of GPT-4 in Radiology. EMNLP 2023: 14414-14445 - [c11]Antonia Tsvetanova, Matthew Sperrin, David A. Jenkins, Niels Peek, Iain E. Buchan, Stephanie L. Hyland, Glen P. Martin:
Compatibility in Missing Data Handling Across the Prediction Model Pipeline: A Simulation Study. MedInfo 2023: 1476-1477 - [i20]Shruthi Bannur, Stephanie L. 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 V. Nori, Javier Alvarez-Valle, Ozan Oktay:
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. CoRR abs/2301.04558 (2023) - [i19]Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland:
Compositional Zero-Shot Domain Transfer with Text-to-Text Models. CoRR abs/2303.13386 (2023) - [i18]Qianchu Liu, Stephanie L. 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, Javier Alvarez-Valle:
Exploring the Boundaries of GPT-4 in Radiology. CoRR abs/2310.14573 (2023) - [i17]Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P. Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle:
MAIRA-1: A specialised large multimodal model for radiology report generation. CoRR abs/2311.13668 (2023) - 2022
- [c10]Edward De Brouwer, Javier Gonzalez, Stephanie L. Hyland:
Predicting the impact of treatments over time with uncertainty aware neural differential equations. AISTATS 2022: 4705-4722 - [c9]Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie L. Hyland, Maria Wetscherek, Tristan Naumann, Aditya V. Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. ECCV (36) 2022: 1-21 - [i16]Edward De Brouwer, Javier González Hernández, Stephanie L. Hyland:
Predicting the impact of treatments over time with uncertainty aware neural differential equations. CoRR abs/2202.11987 (2022) - [i15]Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie L. Hyland, Maria Wetscherek, Tristan Naumann, Aditya V. Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. CoRR abs/2204.09817 (2022) - [i14]Dimitris Spathis, Stephanie L. Hyland:
Looking for Out-of-Distribution Environments in Critical Care: A case study with the eICU Database. CoRR abs/2205.13398 (2022) - 2021
- [c8]Antonia Tsvetanova, Glen P. Martin, Matthew Sperrin, Niels Peek, Iain E. Buchan, Stephanie L. Hyland:
Inconsistencies in handling missing data across stages of prediction modelling: a review of methods used. AMIA 2021 - [c7]Emma Rocheteau, Pietro Liò, Stephanie L. Hyland:
Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit. CHIL 2021: 58-68 - [c6]Antonia Tsvetanova, Matthew Sperrin, Niels Peek, Iain E. Buchan, Stephanie L. Hyland, Glen P. Martin:
Inconsistencies in handling missing data across stages of prediction modelling: a review of methods used. ICHI 2021: 443-444 - [e2]Melanie F. Pradier, Aaron Schein, Stephanie L. Hyland, Francisco J. R. Ruiz, Jessica Zosa Forde:
I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, Virtual Workshop, December 13, 2021. Proceedings of Machine Learning Research 163, PMLR 2021 [contents] - [i13]Matthias Hüser, Martin Faltys, Xinrui Lyu, Chris Barber, Stephanie L. Hyland, Tobias M. Merz, Gunnar Rätsch:
Early prediction of respiratory failure in the intensive care unit. CoRR abs/2105.05728 (2021) - 2020
- [c5]Suproteem K. Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Ioana Bica, Griffin Adams, Stephen Pfohl, Stephanie L. Hyland:
Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. ML4H@NeurIPS 2020: 1-11 - [e1]Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K. Sarkar, Subhrajit Roy, Stephanie L. Hyland:
Machine Learning for Health Workshop, ML4H@NeurIPS 2020, Virtual Event, 11 December 2020. Proceedings of Machine Learning Research 136, PMLR 2020 [contents] - [i12]Emma Rocheteau, Pietro Liò, Stephanie L. Hyland:
Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks. CoRR abs/2006.16109 (2020) - [i11]Emma Rocheteau, Pietro Liò, Stephanie L. Hyland:
Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit. CoRR abs/2007.09483 (2020) - [i10]Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K. Sarkar, Subhrajit Roy, Stephanie L. Hyland:
ML4H Abstract Track 2020. CoRR abs/2011.11554 (2020)
2010 – 2019
- 2019
- [i9]Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean A. Bodenham, Karsten M. Borgwardt, Gunnar Rätsch, Tobias M. Merz:
Machine learning for early prediction of circulatory failure in the intensive care unit. CoRR abs/1904.07990 (2019) - [i8]Stefan G. Stark, Stephanie L. Hyland, Melanie Fernandes Pradier, Kjong-Van Lehmann, Andreas Wicki, Fernando Pérez-Cruz, Julia E. Vogt, Gunnar Rätsch:
Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies. CoRR abs/1904.12973 (2019) - [i7]Stephanie L. Hyland, Shruti Tople:
On the Intrinsic Privacy of Stochastic Gradient Descent. CoRR abs/1912.02919 (2019) - 2018
- [c4]Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Cristóbal Esteban, Gunnar Rätsch, Tobias Merz:
A Machine Learning-based Early Warning System for Circulatory System Deterioration in Intensive Care Unit Patients. AMIA 2018 - [c3]Stephanie L. Hyland, Matthias Hüser, Xinrui Lyu, Martin Faltys, Tobias Merz, Gunnar Rätsch:
Predicting circulatory system deterioration in intensive care unit patients. AIH@IJCAI 2018: 87-92 - [i6]Xinrui Lyu, Matthias Hüser, Stephanie L. Hyland, George Zerveas, Gunnar Rätsch:
Improving Clinical Predictions through Unsupervised Time Series Representation Learning. CoRR abs/1812.00490 (2018) - 2017
- [c2]Stephanie L. Hyland, Gunnar Rätsch:
Learning Unitary Operators with Help From u(n). AAAI 2017: 2050-2058 - [i5]Cristóbal Esteban, Stephanie L. Hyland, Gunnar Rätsch:
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs. CoRR abs/1706.02633 (2017) - 2016
- [c1]Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch:
A Generative Model of Words and Relationships from Multiple Sources. AAAI 2016: 2622-2629 - [i4]Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch:
Knowledge Transfer with Medical Language Embeddings. CoRR abs/1602.03551 (2016) - [i3]Stephanie L. Hyland, Gunnar Rätsch:
Learning Unitary Operators with Help From u(n). CoRR abs/1607.04903 (2016) - [i2]Paulina Grnarova, Florian Schmidt, Stephanie L. Hyland, Carsten Eickhoff:
Neural Document Embeddings for Intensive Care Patient Mortality Prediction. CoRR abs/1612.00467 (2016) - 2015
- [i1]Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch:
A Generative Model of Words and Relationships from Multiple Sources. CoRR abs/1510.00259 (2015)
Coauthor Index
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last updated on 2024-10-07 21:19 CEST by the dblp team
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