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Frank Soboczenski
Frank Soboczenski
Assistant Professor, University of York & Affiliate King's College London
Verified email at york.ac.uk - Homepage
Title
Cited by
Cited by
Year
An ensemble of bayesian neural networks for exoplanetary atmospheric retrieval
AD Cobb, MD Himes, F Soboczenski, S Zorzan, MD O’Beirne, AG Baydin, ...
The astronomical journal 158 (1), 33, 2019
662019
Generating (factual?) narrative summaries of rcts: Experiments with neural multi-document summarization
BC Wallace, S Saha, F Soboczenski, IJ Marshall
AMIA Summits on Translational Science Proceedings 2021, 605, 2021
532021
Trialstreamer: A living, automatically updated database of clinical trial reports
IJ Marshall, B Nye, J Kuiper, A Noel-Storr, R Marshall, R Maclean, ...
Journal of the American Medical Informatics Association 27 (12), 1903-1912, 2020
522020
Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study
F Soboczenski, TA Trikalinos, J Kuiper, RG Bias, BC Wallace, IJ Marshall
BMC Medical Informatics and Decision Making 19, 1-12, 2019
432019
Accurate machine-learning atmospheric retrieval via a neural-network surrogate model for radiative transfer
MD Himes, J Harrington, AD Cobb, AG Baydin, F Soboczenski, ...
The Planetary Science Journal 3 (4), 91, 2022
272022
Forecast-based interference: Modelling multicore interference from observable factors
D Griffin, B Lesage, I Bate, F Soboczenski, RI Davis
Proceedings of the 25th International Conference on Real-Time Networks and …, 2017
232017
A framework for the evaluation of measurement-based timing analyses
B Lesage, D Griffin, F Soboczenski, I Bate, RI Davis
Proceedings of the 23rd international conference on real time and networks …, 2015
222015
State of the evidence: a survey of global disparities in clinical trials
IJ Marshall, V L'Esperance, R Marshall, J Thomas, A Noel-Storr, ...
BMJ global health 6 (1), e004145, 2021
172021
Study of the reliability of statistical timing analysis for real-time systems
D Maxim, F Soboczenski, I Bate, E Tovar
Proceedings of the 23rd international conference on real time and networks …, 2015
152015
On invariance penalties for risk minimization
K Khezeli, A Blaas, F Soboczenski, N Chia, J Kalantari
arXiv preprint arXiv:2106.09777, 2021
142021
Prototyping CRISP: a Causal Relation and Inference Search Platform applied to colorectal cancer data
S Budd, A Blaas, A Hoarfrost, K Khezeli, K D'Silva, F Soboczenski, ...
2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech …, 2021
132021
Increasing accuracy by decreasing presentation quality in transcription tasks
F Soboczenski, P Cairns, AL Cox
Human-Computer Interaction–INTERACT 2013: 14th IFIP TC 13 International …, 2013
112013
Bayesian deep learning for exoplanet atmospheric retrieval
F Soboczenski, MD Himes, MD O'Beirne, S Zorzan, AG Baydin, AD Cobb, ...
arXiv preprint arXiv:1811.03390, 2018
102018
Visualizing magnitude: Graphical number representations help users detect large number entry errors
J Borghouts, F Soboczenski, P Cairns, DP Brumby
Proceedings of the Human Factors and Ergonomics Society Annual Meeting 59 (1 …, 2015
82015
Evaluating mixed criticality scheduling algorithms with realistic workloads
D Griffin, I Bate, B Lesage, F Soboczenski
Proceedings of Workshop on Mixed Criticality (WMC), 2015
82015
Biomonitoring and precision health in deep space supported by artificial intelligence
RT Scott, LM Sanders, EL Antonsen, JJA Hastings, S Park, G Mackintosh, ...
Nature Machine Intelligence 5 (3), 196-207, 2023
72023
In a pilot study, automated real-time systematic review updates were feasible, accurate, and work-saving
IJ Marshall, TA Trikalinos, F Soboczenski, HS Yun, G Kell, R Marshall, ...
Journal of Clinical Epidemiology 153, 26-33, 2023
72023
Biological research and self-driving labs in deep space supported by artificial intelligence
LM Sanders, RT Scott, JH Yang, AA Qutub, H Garcia Martin, DC Berrios, ...
Nature Machine Intelligence 5 (3), 208-219, 2023
62023
Beyond low earth orbit: biomonitoring, artificial intelligence, and precision space health
RT Scott, EL Antonsen, LM Sanders, JJA Hastings, S Park, G Mackintosh, ...
arXiv preprint arXiv:2112.12554, 2021
52021
Machine Learning for Health (ML4H) 2019: What Makes Machine Learning in Medicine Different?
AV Dalca, MBA McDermott, E Alsentzer, SG Finlayson, M Oberst, F Falck, ...
Machine Learning for Health Workshop, 1-9, 2020
42020
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