Article

Lisboa, P, Saralajew, S, Vellido, A, Fern´andez-Domenech, R and Villmann, T (2023) The coming of age of interpretable and explainable machine learning models. Neurocomputing, 535. pp. 25-39. ISSN 0925-2312

Galvain, T, Hill, R, Donegan, S, Lisboa, P, Lip, GYH and Czanner, G (2022) Efficacy and Safety of Anticoagulants in Patients with Atrial Fibrillation and History of Falls or Risk of Falls: A Systematic Review and Multilevel Meta-Analysis. Drug Safety, 45 (11). pp. 1349-1362. ISSN 0114-5916

Aras, S and Lisboa, P (2022) Explainable inflation forecasts by machine learning models. Expert Systems with Applications, 207. ISSN 0957-4174

McCabe, PG, Lisboa, P, Baltzopoulos, V and Olier, I (2022) Externally validated models for first diagnosis and risk of progression of knee osteoarthritis. PloS one, 17 (7). ISSN 1932-6203

Galvain, T, Hill, R, Donegan, S, Lisboa, P, Lip, GYH and Czanner, G (2022) The management of anticoagulants in patients with atrial fibrillation and history of falls or risk of falls: protocol for a systematic review and meta-analysis. Systematic Reviews, 11 (63). ISSN 2046-4053

Llanera, DK, Wilmington, R, Shoo, H, Lisboa, P, Jarman, I, Wong, S, Nizza, J, Sharma, D, Kalathil, D, Rajeev, S, Williams, S, Yadav, R, Qureshi, Z, Narayanan, RP, Furlong, N, Westall, S and Nair, S (2022) Clinical Characteristics of COVID-19 Patients in a Regional Population With Diabetes Mellitus: The ACCREDIT Study. Frontiers in Endocrinology, 12. ISSN 1664-2392

Fergus, P, Chalmers, C, Montañez, CC, Reilly, D, Lisboa, P and Pineles, B (2020) Modelling Segmented Cardiotocography Time-Series Signals Using One-Dimensional Convolutional Neural Networks for the Early Detection of Abnormal Birth Outcomes. IEEE Transactions on Emerging Topics in Computational Intelligence. ISSN 2471-285X

Ackermans, TMA, Francksen, NC, Lees, C, Papatzika, F, Arampatzis, A, Baltzopoulos, V, Lisboa, P, Hollands, MA, O'Brien, TD and Maganaris, CN (2020) Prediction of balance perturbations and falls on stairs in older people using a biomechanical profiling approach: A 12-month longitudinal study. Journals of Gerontology Series A. ISSN 1758-535X

Pogson, MA, Verheul, J, Robinson, MA, Vanrenterghem, J and Lisboa, P (2020) A neural network method to predict task- and step-specific ground reaction force magnitudes from trunk accelerations during running activities. Medical Engineering and Physics, 78. pp. 82-89. ISSN 1350-4533

Casaña-Eslava, RV, Lisboa, P, Ortega-Martorell, S, Jarman, I and Martin-Guerrera, J (2020) Probabilistic quantum clustering. Knowledge-Based Systems. ISSN 0950-7051

Hind, J, Lisboa, P, Hussain, A and Al-Jumeily, D (2019) A Novel Approach to Detecting Epistasis using Random Sampling Regularisation. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17 (5). ISSN 1545-5963

Verheul, J, Warmenhoven, J, Lisboa, P, Gregson, W, Vanrenterghem, J and Robinson, MA (2019) Identifying generalised segmental acceleration patterns that contribute to ground reaction force features across different running tasks. Journal of Science and Medicine in Sport. ISSN 1878-1861

Verheul, J, Nedergaard, NJ, Pogson, MA, Lisboa, P, Gregson, W, Vanrenterghem, J and Robinson, MA (2019) Biomechanical loading during running: can a two mass-spring-damper model be used to evaluate ground reaction forces for high-intensity tasks? Sports Biomechanics. ISSN 1752-6116

Verheul, J, Gregson, W, Lisboa, P, Vanrenterghem, J and Robinson, MA (2018) Whole-body biomechanical load in running-based sports: the validity of estimating ground reaction forces from segmental. Journal of Science and Medicine in Sport. ISSN 1440-2440

Nedergaard, NJ, Verheul, J, Drust, B, Etchells, T, Lisboa, P, Robinson, MA and Vanrenterghem, J (2018) The feasibility of predicting ground reaction forces during running from a trunk accelerometry driven mass-spring-damper model. PeerJ. ISSN 2167-8359

Fergus, P, Montanez, C, Abdulaimma, B, Lisboa, P, Chalmers, C and Pineless, B (2018) Utilising Deep Learning and Genome Wide Association Studies for Epistatic-Driven Preterm Birth Classification in African-American Women. IEEE/ACM Transactions on Computational Biology and Bioinformatics. ISSN 1545-5963

Cashman, S, Korostynska, O, Shaw, A, Lisboa, P and Conroy, L (2017) Detecting the presence and concentration of nitrate in water using microwave spectroscopy. IEEE Sensors Journal (99). ISSN 1530-437X

Van Belle, V, Van Calster, B, Van Huffel, S, Suykens, JAK and Lisboa, P (2016) Explaining Support Vector Machines: A Color Based Nomogram. PLoS One, 11 (10). ISSN 1932-6203

Datson, N, Drust, B, Weston, M, Jarman, I, Lisboa, P and Gregson, W (2016) Match physical performance of elite female soccer players during international competition. Journal of Strength and Conditioning Research. ISSN 1533-4287

Dean, E, Taylor, MJ, Francis, H, Lisboa, P, Appleton, D and Jones, M (2016) A methodological framework for geographic information systems development. Systems Research and Behavioral Science. ISSN 1099-1743

Delgado-Goñi, T, Ortega Martorell, S, Ciezka, M, Olier, I, Candiota, AP, Julià-Sapé, M, Fernández, F, Pumarola, M, Lisboa, P and Arús, C (2016) MRSI-based molecular imaging of therapy response to temozolomide in preclinical glioblastoma using source analysis. NMR in Biomedicine, 29 (6). pp. 732-743. ISSN 1099-1492

Nedergaard, NJ, Robinson, MA, Eusterwiemann, E, Drust, B, Lisboa, P and Vanrenterghem, J (2016) The relationship between whole-body external loading and body-worn accelerometry during team sports movements. International Journal of Sports Physiology and Performance. ISSN 1555-0273

Mocioiu, V, Ortega-Martorell, S, Olier, I, Jablonski, M, Starcukova, J, Lisboa, P, Arús, C and Julià-Sapé, M (2015) From raw data to data-analysis for magnetic resonance spectroscopy - the missing link: jMRUI2XML. BMC Bioinformatics, 16 (378). pp. 1-11. ISSN 1471-2105

Lowsby, R, Gomes, C, Jarman, I, Lisboa, P, Nee, PA, Vardhan, M, Eckersley, T, Saleh, R and Mills, H (2015) Neutrophil to lymphocyte count ratio as an early indicator of blood stream infection in the emergency department. EMERGENCY MEDICINE JOURNAL, 32 (7). ISSN 1472-0205

Lisboa, P, Martín-Guerrero, JD and Vellido, A (2015) Making nonlinear manifold learning models interpretable: The manifold grand tour. Expert Systems with Applications, 42 (22). pp. 8982-8988. ISSN 0957-4174

Kinderman, P, Tai, S, Pontin, E, Schwannauer, M, Jarman, I and Lisboa, P (2015) Causal and mediating factors for anxiety, depression and well-being. BRITISH JOURNAL OF PSYCHIATRY, 206 (6). pp. 456-460. ISSN 0007-1250

Taylor, MJ, Higgins, E, Lisboa, P, Jarman, I and Hussain, A (2015) Community fire prevention via population segmentation modelling. Community Development Journal. ISSN 1468-2656

Hussain, A, Al-Jumeily, D, Radi, N and Lisboa, P (2014) Hybrid Neural Network Predictive-Wavelet Image Compression System. NEUROCOMPUTING, 151. ISSN 0925-2312

Farhadian, M, Lisboa, P, Moghimbeigi, A, Poorolajal, J and Mahjub, H (2014) Supervised wavelet method to predict patient survival from gene expression data. Scientific World Journal, 2014. ISSN 1537-744X

Taylor, MJ, Stables, R, Matata, B, Lisboa, P, Laws, A and Almond, P (2014) Website design: Technical, social and medical issues for self-reporting by elderly patients. HEALTH INFORMATICS JOURNAL, 20 (2). pp. 136-150. ISSN 1460-4582

Taylor, MJ, Higgins, E, Lisboa, P and Arshad, F (2014) Developing a data sharing framework: a case study. Transforming Government: People, Process and Policy, 1 (8). pp. 151-164. ISSN 1750-6174

Ortega-Martorell, S, Ruiz, H, Vellido, A, Olier, I, Romero, E, Julia-Sape, M, Martin, JD, Jarman, I, Arus, C and Lisboa, P (2013) A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data. PLOS ONE, 8 (12). pp. 1-14. ISSN 1932-6203

Van Belle, V and Lisboa, P (2013) White box radial basis function classifiers with component selection for clinical prediction models. Artificial Intelligence in Medicine, 60 (1). pp. 53-64. ISSN 0933-3657

Book Section

Ortega-Martorell, S, Julià-Sapé, M, Lisboa, P and Arús, C (2016) Pattern Recognition Analysis of MR Spectra. In: Griffiths, J and Bottomley, P, (eds.) Handbook of in vivo Magnetic Resonance Spectroscopy. John Wiley & Sons. ISBN 978-1-118-99766-6

Conference or Workshop Item

Walters, B, Ortega Martorell, S, Olier-Caparroso, I and Lisboa, P (2022) Towards interpretable machine learning for clinical decision support. In: Proceedings of the International Joint Conference on Neural Networks . (International Joint Conference on Neural Networks, Padua, Italy).

Olier-Caparroso, I, Sansom, A, Lisboa, P and Ortega-Martorell, S (2021) Using MLP partial responses to explain in-hospital mortality in ICU. In: 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI) . (2020 International Conference on Data Analytics for Business and Industry, 26 October 2020 - 27 October 2020, Sakheer, Bahrain).

Srivastava, M, Olier, I, Riley, P, Lisboa, P and Ortega-Martorell, S (2019) Classifying and Grouping Mammography Images into Communities Using Fisher Information Networks to Assist the Diagnosis of Breast Cancer. In: Advances in Intelligent Systems and Computing , 976. pp. 304-313. (13th International Workshop, WSOM+ 2019, 26th-28th June 2019, Barcelona, Spain).

Riley, P, Olier, I, Rea, M, Lisboa, P and Ortega-Martorell, S (2019) A Voting Ensemble Method to Assist the Diagnosis of Prostate Cancer Using Multiparametric MRI. In: Advances in Intelligent Systems and Computing , 976. (13th International Workshop, WSOM+ 2019, 26th-28th June 2019, Barcelona, Spain).

Khalaf, M, Hussain, A, Al-Jumeily, D, Baker, T, Keight, R, Lisboa, P, Alkafri, A and Fergus, P (2018) A Data Science Methodology Based on Machine Learning Algorithms for Flood Severity Prediction. In: 2018 IEEE Congress on Evolutionary Computation (CEC) . (IEEE Congress on Evolutionary Computation, 08 July 2018 - 13 July 2018, Brazil).

Abdulaimma, B, Hussain, A, Fergus, P, Al-Jumeily, D, Lisboa, P, Huang, D-S and Radi, N (2018) Improving Type 2 Diabetes Phenotypic Classification by Combining Genetics and Conventional Risk Factors. In: 2018 IEEE Congress on Evolutionary Computation (CEC) . (2018 IEEE Congress on Evolutionary Computation (IEEE CEC 2018), 08 July 2018 - 13 April 2018, Brazil).

Harris, B, Dobbins, C, Fairclough, SH and Lisboa, P (2017) Exploring Wearable Devices for Unobtrusive Stress Monitoring. In: ACM International Conference Proceedings Series . (Second International Conference on Internet of Things, Data and Cloud Computing, 22 – 23 March, 2017, Cambridge, UK).

Urda, D, Chambers, SJ, Jarman, I, Lisboa, P, Franco, L and Jerez, JM (2015) Use of q-values to Improve a Genetic Algorithm to Identify Robust Gene Signatures. In: Lecture Notes in Computer Science , 8623. pp. 199-206. (11th International Meeting, CIBB 2014, 26th-28th June 2014, Cambridge, UK).

Chambers, SJ, Jarman, I and Lisboa, P (2015) A framework for initialising a dynamic clustering algorithm: ART2-A. In: Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on . pp. 273-280. (Computational Intelligence and Data Mining (CIDM), 9th-12th December 2014, Orlando, Florida).

Ortega-Martorell, S, Olier, I, Delgado-Goni, T, Ciezka, M, Julià-Sapé, M, Lisboa, P and Arús, C (2015) Semi-supervised source extraction methodology for the nosological imaging of glioblastoma response to therapy. In: CIDM 2014: Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on . pp. 93-98. (2014 IEEE Symposium on Computation Intelligence and Data Mining, 9th-12th December 2014, Orlando, FL).

Ortega-Martorell, S, Olier, I, Julià-Sapé, M, Arús, C and Lisboa, P (2014) Automatic relevance source determination in human brain tumors using Bayesian NMF. In: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) . pp. 99-104. (2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), 9th-12th December 2014, Orlando, Florida).

Harris, B, Dobbins, C, Fairclough, SH and Lisboa, P Measuring Academic Stress ‘In the Wild’ with Wearable Sensors: Removal of Noise from Wearable Sensor Data Using Fir Filters. In: 1st Neuroadaptive Technology Conference 2017 (NAT’17), 19 July 2017 - 21 July 2017, Berlin, Germany. (Accepted)