Andrew A. S. Soltan

According to our database, Andrew A. S. Soltan authored at least 18 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Geometric Characterisation and Structured Trajectory Surrogates for Clinical Dataset Condensation.

Pafue Christy Nganjimi, Andrew A. S. Soltan, Danielle Belgrave, Lei A. Clifton, David A. Clifton, Anshul Thakur

CoRR, April, 2026

Learning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling Under Data-View Heterogeneity.

Soheila Molaei, Anshul Thakur, Lei A. Clifton, Andrew A. S. Soltan, Patrick Schwab, Danielle Belgrave, Kim Branson, David A. Clifton

IEEE J. Biomed. Health Informatics, March, 2026

Democratising Clinical AI through Dataset Condensation for Classical Clinical Models.

Anshul Thakur, Soheila Molaei, Pafue Christy Nganjimi, Joshua Fieggen, Andrew A. S. Soltan, Danielle Belgrave, Lei A. Clifton, David A. Clifton

CoRR, March, 2026

Neuro-Symbolic Federated Learning over Heterogeneous Data-Views: A Structured Approach to Distributive EHR Modelling.

Soheila Molaei, Bahareh Fatemi, Anshul Thakur, Andrew A. S. Soltan, Fazle Rabbi, Andreas L. Opdahl, Kim Branson, Patrick Schwab, Danielle Belgrave, David A. Clifton

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Improving Clinical Dataset Condensation with Mode Connectivity-based Trajectory Surrogates.

Pafue Christy Nganjimi, Andrew A. S. Soltan, Danielle Belgrave, Lei A. Clifton, David A. Clifton, Anshul Thakur

CoRR, October, 2025

High-performance automated abstract screening with large language model ensembles.

Rohan Sanghera, Arun James Thirunavukarasu, Marc El Khoury, Jessica O'Logbon, Yuqing Chen, Archie Watt, Mustafa Mahmood, Hamid Butt, George Nishimura, Andrew A. S. Soltan

J. Am. Medical Informatics Assoc., 2025

DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research.

Louis J. M. Aslett, Andreea Avramescu, Nicholas Bakewell, Isabel Birds, Louise Bowler, Michael P. J. Camilleri, Sheng-Chia Chung, David A. Clifton, Samuel N. Cohen, Nathan Constantine-Cooke, Eric G. Daub, Shaun M. Davidson, Spiros C. Denaxas, Karla Diaz-Ordaz, Richard Feltbower, Suzy Gallier, Stephen Gardiner, Francesca Gasperoni, Robert J. B. Goudie, Rebecca E. Green, Marlous S. Hall, Chris Holmes, John R. Hurst, Mark M. Iles, João Jorge, Emma Karoune, Ruth H. Keogh, Ruairidh King, Ruth King, Paul D. W. Kirk, Roman Klapaukh, Samaneh Kouchaki, Alvina Grace Lai, Nathan Lea, Clemence Leyrat, Kezhi Li, Watjana Lilaonitkul, Huiqi Y. Lu, Terry Lyons, Ann-Marie Mallon, Andrew A. Manderson, Nicolò Margaritella, Joshua Matteson, Sam Morley, Hannah Nicholls, Martin T. O'Reilly, Christina Pagel, Edward Palmer, Jack Roberts, Timothy J. Roberts, David S. Robertson, James Robinson, Patrick Rockenschaub, Roy A. Ruddle, Elizabeth Sapey, Luis Santos, Andrew A. S. Soltan, Fang Gao-Smith, Colin Starr, Oliver Strickson, Li Su, Mia S. Tackney, Johan Hilge Thygesen, Ana Torralbo, Alice M. Turner, Catalina A. Vallejos, Chenyang Wang, Kirstie J. Whitaker, Tony Whitehouse, David R. Westhead, Wai Keong Wong, Yue Wu, Lingyi Yang, Xiaoxu Zou

Data, 2025

2024

Addressing label noise for electronic health records: insights from computer vision for tabular data.

Jenny Yang, Hagen Triendl, Andrew A. S. Soltan, Mangal Prakash, David A. Clifton

BMC Medical Informatics Decis. Mak., December, 2024

Deep reinforcement learning for multi-class imbalanced training: applications in healthcare.

Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S. Lachapelle, Andrew A. S. Soltan, David W. Eyre, Lei Lu, David A. Clifton

Mach. Learn., May, 2024

Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare.

Anshul Thakur, Soheila Molaei, Pafue Christy Nganjimi, Andrew A. S. Soltan, Patrick Schwab, Kim Branson, David A. Clifton

npj Digit. Medicine, 2024

Publisher Correction: Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare.

Anshul Thakur, Soheila Molaei, Pafue Christy Nganjimi, Fenglin Liu, Andrew A. S. Soltan, Patrick Schwab, Kim Branson, David A. Clifton

npj Digit. Medicine, 2024

Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention Networks.

Soheila Molaei, Anshul Thakur, Ghazaleh Niknam, Andrew A. S. Soltan, Hadi Zare, David A. Clifton

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning.

Jenny Yang, Andrew A. S. Soltan, David W. Eyre, David A. Clifton

Nat. Mac. Intell., August, 2023

Privacy-Aware Early Detection of COVID-19 Through Adversarial Training.

Omid Rohanian, Samaneh Kouchaki, Andrew A. S. Soltan, Jenny Yang, Morteza Rohanian, Yang Yang, David A. Clifton

IEEE J. Biomed. Health Informatics, March, 2023

An adversarial training framework for mitigating algorithmic biases in clinical machine learning.

Jenny Yang, Andrew A. S. Soltan, David W. Eyre, Yang Yang, David A. Clifton

npj Digit. Medicine, 2023

2022

Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening.

Jenny Yang, Andrew A. S. Soltan, David A. Clifton

npj Digit. Medicine, 2022

Deep Reinforcement Learning for Multi-class Imbalanced Training.

Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S. Lachapelle, Andrew A. S. Soltan, David A. Clifton

CoRR, 2022

2017

The difficult legacy of Turing's wager.

Andrew Thwaites, Andrew A. S. Soltan, Eric Wieser, Ian Nimmo-Smith

J. Comput. Neurosci., 2017