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2020 – today
- 2023
[c78]Asal Khoshravan Azar, Barbara Draghi, Ylenia Rotalinti, Puja Myles, Allan Tucker
:
The Impact of Bias on Drift Detection in AI Health Software. AIME 2023: 313-322- [c77]Ferdoos Hossein Nezhad, Ylenia Rotalinti, Puja Myles, Allan Tucker:
Privacy Assessment of Synthetic Patient Data. CBMS 2023: 1-6 - [c76]Dima R. Alattal, Zhenchen Wang, Puja Myles, Allan Tucker:
Creating Synthetic Geospatial Patient Data to Mimic Real Data Whilst Preserving Privacy: *2022 35th International Symposium on Computer-Based Medical Systems (CBMS). CBMS 2023: 7-12 - [e5]Jose M. Juarez, Mar Marcos, Gregor Stiglic, Allan Tucker:
Artificial Intelligence in Medicine - 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Portorož, Slovenia, June 12-15, 2023, Proceedings. Lecture Notes in Computer Science 13897, Springer 2023, ISBN 978-3-031-34343-8 [contents] - 2022
- [j40]Leila Yousefi, Allan Tucker:
Identifying latent variables in Dynamic Bayesian Networks with bootstrapping applied to Type 2 Diabetes complication prediction. Intell. Data Anal. 26(2): 501-524 (2022) - [j39]Allan Tucker, Thomas George Kannampallil, Samah Jarad Fodeh, Mor Peleg:
New JBI policy emphasizes clinically-meaningful novel machine learning methods. J. Biomed. Informatics 127: 104003 (2022) - [c75]Afees Adegoke Odebode, Allan Tucker, Mahir Arzoky, Stephen Swift:
Estimating the Optimal Number of Clusters from Subsets of Ensembles. DATA 2022: 383-391 - [c74]Marinela Branescu, Stephen Swift, Allan Tucker:
A Comparison of Convolutional Neural Networks and Traditional Feature-Based Classification Applied to Leukaemia Image Analysis. ICIMTH 2022: 545-550 - [c73]Mashael Al-Luhaybi, Stephen Swift, Steve Counsell, Allan Tucker:
Exploring the Explicit Modelling of Bias in Machine Learning Classifiers: A Deep Multi-label ConvNet Approach. ICMLA 2022: 1799-1806 - [c72]Toyah Overton, Allan Tucker, Tim James, Dimitar Hristozov:
dunXai: DO-U-Net for Explainable (Multi-label) Image Classification - Applications to Biomedical Images. IDA 2022: 212-224 - [c71]Biraja Ghoshal, Bhargab Ghoshal, Allan Tucker:
Leveraging Uncertainty in Deep Learning for Pancreatic Adenocarcinoma Grading. MIUA 2022: 565-577 - [c70]Fawzia Zehra Kara-Isitt, Stephen Swift, Allan Tucker:
Intelligently Detecting Information Online-Weaponisation Trends (IDIOT). PKDD/ECML Workshops (1) 2022: 197-214 - [c69]Ylenia Rotalinti, Allan Tucker, Michael Lonergan, Puja Myles, Richard Branson:
Detecting Drift in Healthcare AI Models Based on Data Availability. PKDD/ECML Workshops (2) 2022: 243-258 - [i7]Biraja Ghoshal, Allan Tucker:
On Calibrated Model Uncertainty in Deep Learning. CoRR abs/2206.07795 (2022) - [i6]Biraja Ghoshal, Bhargab Ghoshal, Allan Tucker:
Leveraging Uncertainty in Deep Learning for Pancreatic Adenocarcinoma Grading. CoRR abs/2206.08787 (2022) - 2021
- [j38]Biraja Ghoshal, Allan Tucker, Bal Sanghera, Wai Lup Wong:
Estimating uncertainty in deep learning for reporting confidence to clinicians in medical image segmentation and diseases detection. Comput. Intell. 37(2): 701-734 (2021) - [j37]Zhenchen Wang, Puja Myles, Allan Tucker:
Generating and evaluating cross-sectional synthetic electronic healthcare data: Preserving data utility and patient privacy. Comput. Intell. 37(2): 819-851 (2021) - [j36]Leila Yousefi, Stephen Swift, Mahir Arzoky, Lucia Saachi, Luca Chiovato, Allan Tucker:
Opening the black box: Personalizing type 2 diabetes patients based on their latent phenotype and temporal associated complication rules. Comput. Intell. 37(4): 1460-1498 (2021) - [c68]Biraja Ghoshal, Stephen Swift, Allan Tucker:
Bayesian Deep Active Learning for Medical Image Analysis. AIME 2021: 36-42 - [c67]Bhargab Ghoshal, Biraja Ghoshal, Stephen Swift, Allan Tucker:
Uncertainty Estimation in SARS-CoV-2 B-Cell Epitope Prediction for Vaccine Development. AIME 2021: 361-366 - [c66]Seyed Erfan Sajjadi, Allan Tucker:
Exploiting Clinical Staging Data to Constrain Pseudo-Time Modelling of Disease Progression. CBMS 2021: 241-246 - [c65]Zhenchen Wang, Puja Myles, Anu Jain, James L. Keidel, Roberto Liddi, Lucy Mackillop, Carmelo Velardo, Allan Tucker:
Evaluating a Longitudinal Synthetic Data Generator using Real World Data. CBMS 2021: 259-264 - [c64]Biraja Ghoshal, Allan Tucker:
On Cost-Sensitive Calibrated Uncertainty in Deep Learning: An application on COVID-19 detection. CBMS 2021: 503-509 - [c63]Biraja Ghoshal, Allan Tucker:
Hyperspherical Weight Uncertainty in Neural Networks. IDA 2021: 3-11 - [c62]Barbara Draghi, Zhenchen Wang, Puja Myles, Allan Tucker:
BayesBoost: Identifying and Handling Bias Using Synthetic Data Generators. LIDTA@ECML/PKDD 2021: 49-62 - [e4]Allan Tucker, Pedro Henriques Abreu, Jaime S. Cardoso, Pedro Pereira Rodrigues, David Riaño:
Artificial Intelligence in Medicine - 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, Virtual Event, June 15-18, 2021, Proceedings. Lecture Notes in Computer Science 12721, Springer 2021, ISBN 978-3-030-77210-9 [contents] - [i5]Bhargab Ghoshal, Biraja Ghoshal, Stephen Swift, Allan Tucker:
Uncertainty Estimation in SARS-CoV-2 B-cell Epitope Prediction for Vaccine Development. CoRR abs/2103.11214 (2021) - 2020
- [j35]Arianna Dagliati, Nophar Geifman, Niels Peek, John H. Holmes, Lucia Sacchi, Riccardo Bellazzi, Seyed Erfan Sajjadi, Allan Tucker:
Using topological data analysis and pseudo time series to infer temporal phenotypes from electronic health records. Artif. Intell. Medicine 108: 101930 (2020) - [j34]Fabio Clarizia, Francesco Colace, Massimo De Santo, Marco Lombardi, Francesco Pascale, Domenico Santaniello, Allan Tucker:
A multilevel graph approach for rainfall forecasting: A preliminary study case on London area. Concurr. Comput. Pract. Exp. 32(8) (2020) - [j33]Allan Tucker, Zhenchen Wang, Ylenia Rotalinti, Puja Myles:
Generating high-fidelity synthetic patient data for assessing machine learning healthcare software. npj Digit. Medicine 3 (2020) - [c61]Andrea Capiluppi, Nemitari Ajienka, Nour Ali, Mahir Arzoky, Steve Counsell, Giuseppe Destefanis, Alina Dana Miron, Bhaveet Nagaria, Rumyana Neykova, Martin J. Shepperd, Stephen Swift, Allan Tucker:
Using the Lexicon from Source Code to Determine Application Domain. EASE 2020: 110-119 - [c60]Biraja Ghoshal, Cecilia Lindskog, Allan Tucker:
Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics. IDA 2020: 223-234 - [c59]Toyah Overton, Allan Tucker:
DO-U-Net for Segmentation and Counting - Applications to Satellite and Medical Images. IDA 2020: 391-403 - [c58]Benjamin C. Evans, Allan Tucker, Oliver R. Wearn, Chris Carbone:
Reasoning About Neural Network Activations: An Application in Spatial Animal Behaviour from Camera Trap Classifications. PKDD/ECML Workshops 2020: 26-37 - [c57]Juan de Benedetti, Namir Oues, Zhenchen Wang, Puja Myles, Allan Tucker:
Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks. PKDD/ECML Workshops 2020: 38-47 - [c56]Seyed Erfan Sajjadi, Barbara Draghi, Lucia Sacchi, Arianna Dagliati, John H. Holmes, Allan Tucker:
Building Trajectories Over Topology with TDA-PTS: An Application in Modelling Temporal Phenotypes of Disease. PKDD/ECML Workshops 2020: 48-61 - [i4]Biraja Ghoshal, Allan Tucker:
Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection. CoRR abs/2003.10769 (2020)
2010 – 2019
- 2019
- [j32]Ana D. Maldonado, Laura Uusitalo, Allan Tucker, Thorsten Blenckner, Pedro Aguilera Aguilera, Antonio Salmerón:
Prediction of a complex system with few data: Evaluation of the effect of model structure and amount of data with dynamic bayesian network models. Environ. Model. Softw. 118: 281-297 (2019) - [j31]Mohd Zairul Mazwan Bin Jilani, Allan Tucker, Stephen Swift:
An application of generalised simulated annealing towards the simultaneous modelling and clustering of glaucoma. J. Heuristics 25(6): 933-957 (2019) - [j30]Marco Scutari, Claudia Vitolo, Allan Tucker:
Learning Bayesian networks from big data with greedy search: computational complexity and efficient implementation. Stat. Comput. 29(5): 1095-1108 (2019) - [c55]Mashael Al-Luhaybi, Leila Yousefi, Stephen Swift, Steve Counsell, Allan Tucker:
Predicting Academic Performance: A Bootstrapping Approach for Learning Dynamic Bayesian Networks. AIED (1) 2019: 26-36 - [c54]Arianna Dagliati, Nophar Geifman, Niels Peek, John H. Holmes, Lucia Sacchi, Seyed Erfan Sajjadi, Allan Tucker:
Inferring Temporal Phenotypes with Topological Data Analysis and Pseudo Time-Series. AIME 2019: 399-409 - [c53]Bashir I. Dodo, Yongmin Li, Allan Tucker, Djibril Kaba, Xiaohui Liu:
Retinal OCT Segmentation Using Fuzzy Region Competition and Level Set Methods. CBMS 2019: 93-98 - [c52]Zhenchen Wang, Puja Myles, Allan Tucker:
Generating and Evaluating Synthetic UK Primary Care Data: Preserving Data Utility & Patient Privacy. CBMS 2019: 126-131 - [c51]Leila Yousefi, Stephen Swift, Mahir Arzoky, Lucia Sacchi, Luca Chiovato, Allan Tucker:
Opening the Black Box: Exploring Temporal Pattern of Type 2 Diabetes Complications in Patient Clustering Using Association Rules and Hidden Variable Discovery. CBMS 2019: 198-203 - [c50]Biraja Ghoshal, Allan Tucker, Bal Sanghera, Wai Lup Wong:
Estimating Uncertainty in Deep Learning for Reporting Confidence to Clinicians when Segmenting Nuclei Image Data. CBMS 2019: 318-324 - [c49]Awad Alsaid Alyousef, Svetlana I. Nihtyanova, Christopher P. Denton, Pietro Bosoni, Riccardo Bellazzi, Allan Tucker:
Latent Class Multi-Label Classification to Identify Subclasses of Disease for Improved Prediction. CBMS 2019: 535-538 - [c48]Francesco Colace, Massimo De Santo, Marco Lombardi, Francesco Pascale, Domenico Santaniello, Allan Tucker:
A Multilevel Graph Approach for Predicting Bicycle Usage in London Area. ICICT (2) 2019: 353-362 - [c47]Martin J. Shepperd, Yuchen Guo, Ning Li, Mahir Arzoky, Andrea Capiluppi, Steve Counsell, Giuseppe Destefanis, Stephen Swift, Allan Tucker, Leila Yousefi:
The Prevalence of Errors in Machine Learning Experiments. IDEAL (1) 2019: 102-109 - [i3]Martin J. Shepperd, Yuchen Guo, Ning Li, Mahir Arzoky, Andrea Capiluppi, Steve Counsell, Giuseppe Destefanis, Stephen Swift, Allan Tucker, Leila Yousefi:
The Prevalence of Errors in Machine Learning Experiments. CoRR abs/1909.04436 (2019) - 2018
- [j29]Laura Uusitalo, Maciej T. Tomczak, Bärbel Müller-Karulis, Ivars Putnis, Neda Trifonova, Allan Tucker:
Hidden variables in a Dynamic Bayesian Network identify ecosystem level change. Ecol. Informatics 45: 9-15 (2018) - [j28]Awad Alsaid Alyousef, Svetlana I. Nihtyanova, Christopher P. Denton, Pietro Bosoni, Riccardo Bellazzi, Allan Tucker:
Nearest Consensus Clustering Classification to Identify Subclasses and Predict Disease. J. Heal. Informatics Res. 2(4): 402-422 (2018) - [c46]Leila Yousefi, Stephen Swift, Mahir Arzoky, Lucia Sacchi, Luca Chiovato, Allan Tucker:
Opening the Black Box: Discovering and Explaining Hidden Variables in Type 2 Diabetic Patient Modelling. BIBM 2018: 1040-1044 - [c45]Leila Yousefi, Allan Tucker, Mashael Al-Luhaybi, Lucia Sacchi, Riccardo Bellazzi, Luca Chiovato:
Predicting Disease Complications Using a Stepwise Hidden Variable Approach for Learning Dynamic Bayesian Networks. CBMS 2018: 106-111 - [c44]Nicky Nicolson, Alan Paton, Sarah Phillips, Allan Tucker:
Specimens as Research Objects: Reconciliation Across Distributed Repositories to Enable Metadata Propagation. eScience 2018: 125-135 - [c43]Francesco Colace, Marco Lombardi, Francesco Pascale, Domenico Santaniello, Allan Tucker, Paolo Villani:
MuG: A Multilevel Graph Representation for Big Data Interpretation. HPCC/SmartCity/DSS 2018: 1408-1413 - [c42]Roja Ahmadi, Robert D. Macredie, Allan Tucker:
Intrusion Detection Using Transfer Learning in Machine Learning Classifiers Between Non-cloud and Cloud Datasets. IDEAL (1) 2018: 556-566 - [c41]Samy Ayed, Mahir Arzoky, Stephen Swift, Steve Counsell, Allan Tucker:
An Exploratory Study of the Inputs for Ensemble Clustering Technique as a Subset Selection Problem. IntelliSys (1) 2018: 1041-1055 - [i2]Nicky Nicolson, Alan Paton, Sarah Phillips, Allan Tucker:
Specimens as research objects: reconciliation across distributed repositories to enable metadata propagation. CoRR abs/1809.07725 (2018) - 2017
- [j27]Allan Tucker, Yuanxi Li, David Garway-Heath:
Updating Markov models to integrate cross-sectional and longitudinal studies. Artif. Intell. Medicine 77: 23-30 (2017) - [j26]Allan Tucker, Yuanxi Li, David Garway-Heath:
Reprint of "Updating Markov models to integrate cross-sectional and longitudinal studies". Artif. Intell. Medicine 81: 33-40 (2017) - [c40]Steve Counsell, Stephen Swift, Allan Tucker:
A Deconstructed Replication of a Time of Test Study Using the AGIS Metric. CBMS 2017: 103-104 - [c39]Leila Yousefi, Lucia Sacchi, Riccardo Bellazzi, Luca Chiovato, Allan Tucker:
Predicting Comorbidities Using Resampling and Dynamic Bayesian Networks with Latent Variables. CBMS 2017: 205-206 - [c38]Nicky Nicolson, Allan Tucker:
Identifying Novel Features from Specimen Data for the Prediction of Valuable Collection Trips. IDA 2017: 235-246 - [e3]Niall M. Adams, Allan Tucker, David John Weston:
Advances in Intelligent Data Analysis XVI - 16th International Symposium, IDA 2017, London, UK, October 26-28, 2017, Proceedings. Lecture Notes in Computer Science 10584, Springer 2017, ISBN 978-3-319-68764-3 [contents] - [i1]Danila Vella, Allan Tucker, Riccardo Bellazzi:
Stability analysis of MTopGO for module identification in PPI networks. PeerJ Prepr. 5: e3289 (2017) - 2016
- [j25]Chiara Franco, Leanne Appleby Hepburn, David J. Smith, Stephen Nimrod, Allan Tucker:
A Bayesian Belief Network to assess rate of changes in coral reef ecosystems. Environ. Model. Softw. 80: 132-142 (2016) - [j24]Claudia Vitolo, Andrew Russell, Allan Tucker:
rdefra: Interact with the UK AIR Pollution Database from DEFRA. J. Open Source Softw. 1(4): 51 (2016) - [c37]Mohd Zairul Mazwan Bin Jilani, Allan Tucker, Stephen Swift:
Simultaneous Modelling and Clustering of Visual Field Data. CBMS 2016: 213-218 - [c36]Pietro Bosoni, Allan Tucker, Riccardo Bellazzi, Svetlana I. Nihtyanova, Christopher P. Denton:
Combining Unsupervised and Supervised Learning for Discovering Disease Subclasses. CBMS 2016: 225-226 - [c35]Steve Counsell, Stephen Swift, Allan Tucker:
The AGIS Metric and Time of Test: A Replication Study. CBMS 2016: 269-270 - [c34]Alya Al Nasseri, Faek Menla Ali, Allan Tucker:
Good news and bad news: Do online investor sentiments reaction to return news asymmetric? MIDAS@PKDD/ECML 2016: 55-66 - 2015
- [j23]Neda Trifonova, Andrew Kenny, David L. Maxwell, Daniel Duplisea, Jose A. Fernandes, Allan Tucker:
Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology. Ecol. Informatics 30: 142-158 (2015) - [j22]Alya Al Nasseri, Allan Tucker, Sergio de Cesare:
Quantifying StockTwits semantic terms' trading behavior in financial markets: An effective application of decision tree algorithms. Expert Syst. Appl. 42(23): 9192-9210 (2015) - [j21]Michael James Scott, Steve Counsell, Stanislao Lauria, Stephen Swift, Allan Tucker, Martin J. Shepperd, Gheorghita Ghinea:
Enhancing Practice and Achievement in Introductory Programming With a Robot Olympics. IEEE Trans. Educ. 58(4): 249-254 (2015) - [c33]Allan Tucker, Yuanxi Li:
Updating Stochastic Networks to Integrate Cross-Sectional and Longitudinal Studies. AIME 2015: 113-122 - [p3]Agnieszka Onisko, Allan Tucker, Marek J. Druzdzel:
Prediction and Prognosis of Health and Disease. Foundations of Biomedical Knowledge Representation 2015: 181-188 - [p2]Allan Tucker, Yuanxi Li, Stefano Ceccon, Stephen Swift:
Trajectories Through the Disease Process: Cross Sectional and Longitudinal Studies. Foundations of Biomedical Knowledge Representation 2015: 189-205 - 2014
- [j20]Lucia Sacchi, Allan Tucker, Steve Counsell, David Garway-Heath, Stephen Swift:
Improving predictive models of glaucoma severity by incorporating quality indicators. Artif. Intell. Medicine 60(2): 103-112 (2014) - [j19]Stefano Ceccon, David F. Garway-Heath, David P. Crabb, Allan Tucker:
Exploring Early Glaucoma and the Visual Field Test: Classification and Clustering Using Bayesian Networks. IEEE J. Biomed. Health Informatics 18(3): 1008-1014 (2014) - [c32]Yuanxi Li, Allan Tucker:
Integrating Clinical Data from Cross-Sectional and Longitudinal Studies. CBMS 2014: 465-466 - [c31]Alya Al Nasseri, Allan Tucker, Sergio de Cesare:
Big Data Analysis of StockTwits to Predict Sentiments in the Stock Market. Discovery Science 2014: 13-24 - [c30]Neda Trifonova, Daniel Duplisea, Andrew Kenny, David L. Maxwell, Allan Tucker:
Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology. Discovery Science 2014: 301-312 - [c29]Steve Counsell, Allan Tucker, Stephen Swift, Guy Fitzgerald, Jason Peters:
Comparing Pre-defined Software Engineering Metrics with Free-Text for the Prediction of Code 'Ripples'. IDA 2014: 61-71 - [c28]Neda Trifonova, Daniel Duplisea, Andrew Kenny, Allan Tucker:
A Spatio-temporal Bayesian Network Approach for Revealing Functional Ecological Networks in Fisheries. IDA 2014: 298-308 - [c27]Allan Tucker, Don Kirkup:
Extracting Predictive Models from Marked-Up Free-Text Documents at the Royal Botanic Gardens, Kew, London. IDA 2014: 309-320 - 2013
- [j18]Yuanxi Li, Stephen Swift, Allan Tucker:
Modelling and analysing the dynamics of disease progression from cross-sectional studies. J. Biomed. Informatics 46(2): 266-274 (2013) - [c26]Valeria Bo, Artem Lysenko, Mansoor A. S. Saqi, Dimah Z. Habash, Allan Tucker:
Integrating Multiple Studies of Wheat Microarray Data to Identify Treatment-Specific Regulatory Networks. IDA 2013: 104-115 - [c25]Stelios Pavlidis, Stephen Swift, Allan Tucker, Steve Counsell:
The Modelling of Glaucoma Progression through the Use of Cellular Automata. IDA 2013: 322-332 - [e2]Allan Tucker, Frank Höppner, Arno Siebes, Stephen Swift:
Advances in Intelligent Data Analysis XII - 12th International Symposium, IDA 2013, London, UK, October 17-19, 2013. Proceedings. Lecture Notes in Computer Science 8207, Springer 2013, ISBN 978-3-642-41397-1 [contents] - 2012
- [j17]Mahir Arzoky, Stephen Swift, Allan Tucker, James Cain:
A Seeded Search for the Modularisation of Sequential Software Versions. J. Object Technol. 11(2): 6: 1-27 (2012) - [e1]Jaakko Hollmén, Frank Klawonn, Allan Tucker:
Advances in Intelligent Data Analysis XI - 11th International Symposium, IDA 2012, Helsinki, Finland, October 25-27, 2012. Proceedings. Lecture Notes in Computer Science 7619, Springer 2012, ISBN 978-3-642-34155-7 [contents] - 2011
- [j16]Seyed Yahya Anvar, Allan Tucker, Veronica Vinciotti, Andrea Venema, Gert-Jan B. van Ommen, Silvere M. van der Maarel, Vered Raz, Peter A. C. 't Hoen:
Interspecies Translation of Disease Networks Increases Robustness and Predictive Accuracy. PLoS Comput. Biol. 7(11) (2011) - [c24]Mahir Arzoky, Stephen Swift, Allan Tucker, James Cain:
Munch: An Efficient Modularisation Strategy to Assess the Degree of Refactoring on Sequential Source Code Checkings. ICST Workshops 2011: 422-429 - [c23]Stefano Ceccon, David Garway-Heath, David P. Crabb, Allan Tucker:
The Dynamic Stage Bayesian Network: Identifying and Modelling Key Stages in a Temporal Process. IDA 2011: 101-112 - [c22]Fadratul Hafinaz Hassan, Allan Tucker:
Automatic Layout Design Solution. IDA 2011: 198-209 - [c21]Allan Tucker, Daniel Duplisea:
Integrating Marine Species Biomass Data by Modelling Functional Knowledge. IDA 2011: 352-363 - [p1]Stefano Ceccon, David Garway-Heath, David P. Crabb, Allan Tucker:
Ensembles of Bayesian Network Classifiers Using Glaucoma Data and Expertise. Ensembles in Machine Learning Applications 2011: 133-150 - 2010
- [j15]Seyed Yahya Anvar, Peter A. C. 't Hoen, Allan Tucker:
The identification of informative genes from multiple datasets with increasing complexity. BMC Bioinform. 11: 32 (2010) - [j14]Weiguo Sheng, Allan Tucker, Xiaohui Liu:
A niching genetic k-means algorithm and its applications to gene expression data. Soft Comput. 14(1): 9-19 (2010) - [j13]Allan Tucker, David Garway-Heath:
The pseudotemporal bootstrap for predicting glaucoma from cross-sectional visual field data. IEEE Trans. Inf. Technol. Biomed. 14(1): 79-85 (2010) - [c20]Fadratul Hafinaz Hassan, Allan Tucker:
Using Cellular Automata Pedestrian Flow Statistics with Heuristic Search to Automatically Design Spatial Layout. ICTAI (2) 2010: 32-37 - [c19]Fadratul Hafinaz Hassan, Allan Tucker:
Using Uniform Crossover to Refine Simulated Annealing Solutions for Automatic Design of Spatial Layouts. IJCCI (ICEC) 2010: 373-379 - [c18]Allan Tucker, Stephen Swift, Steve Counsell, Simon Kent, John Dickie, Kenwin Liu, Robert Turner:
Data Mining the Millennium Seedbank at Kew. ICDM (Workshops) 2010: 85-94
2000 – 2009
- 2009
- [j12]Emma Steele, Allan Tucker, Peter A. C. 't Hoen, Martijn J. Schuemie:
Literature-based priors for gene regulatory networks. Bioinform. 25(14): 1768-1774 (2009) - [c17]Emma Steele, Allan Tucker:
Selecting and Weighting Data for Building Consensus Gene Regulatory Networks. IDA 2009: 190-201 - [c16]James Cain, Steve Counsell, Stephen Swift, Allan Tucker:
An Application of Intelligent Data Analysis Techniques to a Large Software Engineering Dataset. IDA 2009: 261-272 - 2008
- [j11]Emma Steele, Allan Tucker:
Consensus and Meta-analysis regulatory networks for combining multiple microarray gene expression datasets. J. Biomed. Informatics 41(6): 914-926 (2008) - 2007
- [c15]Allan Tucker, Stephen Swift, Jason Crampton:
Efficiency updates for the restricted growth function GA for grouping problems. GECCO 2007: 1536 - [c14]