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  Predictability of the coherent-noise model and its applications

  Sarlis, N. V. & Christopoulos, S. R. G., 25 May 2012, In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. 85, 5, 051136.

  Research output: Contribution to journal › Article › peer-review
  8 Citations (Scopus)

• Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment

  Gupta, R., Lau Chi Keung, M. & Nyakabawo, W., 29 Jan 2020, In: Journal of Reviews on Global Economics. 9, p. 30-46 17 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

• Predicting and Preventing: Developing a Risk Assessment Mechanism for Residential Housing

  Armitage, R., Jul 2006, In: Crime Prevention and Community Safety. 8, 3, p. 137-149 13 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  36 Citations (Scopus)

• Predicting and Preventing the Theft of Electronic Products

  Armitage, R. & Pease, K., Mar 2008, In: European Journal on Criminal Policy and Research. 14, 1, p. 11-37 27 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  15 Citations (Scopus)

• Predicting annual illuminance and operative temperature in residential buildings using artificial neural networks

  Kristiansen, T., Jamil, F., Hameed, I. A. & Hamdy, M., 1 Jun 2022, In: Building and Environment. 217, 14 p., 109031.

  Research output: Contribution to journal › Article › peer-review
  7 Citations (Scopus)

• Predicting change for individual psychotherapy clients based on their nearest neighbors

  Lutz, W., Leach, C., Barkham, M., Lucock, M., Stiles, W. B., Evans, C., Noble, R. & Iveson, S., Oct 2005, In: Journal of Consulting and Clinical Psychology. 73, 5, p. 904-913 10 p.

  Research output: Contribution to journal › Article › peer-review
  106 Citations (Scopus)

• Predicting community violence from patients discharged from acute mental health units in England

  Doyle, M., Carter, S., Shaw, J. & Dolan, M., 1 Apr 2012, In: Social Psychiatry and Psychiatric Epidemiology. 47, 4, p. 627-637 11 p.

  Research output: Contribution to journal › Article › peer-review
  35 Citations (Scopus)

• Predicting community violence from patients discharged from mental health services

  Doyle, M. & Dolan, M., Dec 2006, In: British Journal of Psychiatry. 189, 6, p. 520-526 7 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  113 Citations (Scopus)

• Predicting cooperation in competitive conditions: The role of sportspersonship, moral competence, and emotional intelligence

  Perry, J. L. & Clough, P. J., 1 Jul 2017, In: Psychology of Sport and Exercise. 31, p. 88-92 5 p.

  Research output: Contribution to journal › Article › peer-review
  6 Citations (Scopus)

• Predicting creditworthiness in retail banking with limited scoring data

  Abdou, H. A., Tsafack, M. D. D., Ntim, C. G. & Baker, R. D., 1 Jul 2016, In: Knowledge-Based Systems. 103, p. 89-103 15 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  37 Citations (Scopus)

• Predicting Criminality? Risk Factors, Neighbourhood Influence and Desistance

  Webster, C., Macdonald, R. & Simpson, M., 1 Apr 2006, In: Youth Justice. 6, 1, p. 7-22 16 p.

  Research output: Contribution to journal › Article › peer-review
  76 Citations (Scopus)

• Predicting Drug Review Polarity Using the Combination Model of Multi-sense Word Embedding and Fuzzy Latent Dirichlet Allocation (FLDA)

  Song, S. & Johnson, A., 31 Oct 2023, In: IEEE Access. 11, p. 118538-118546 9 p., 10290872.

  Research output: Contribution to journal › Article › peer-review

  Open Access

• Predicting GP visits: A multinomial logistic regression investigating GP visits amongst a cohort of UK patients living with Myalgic encephalomyelitis

  Walsh, R. S., Denovan, A., Drinkwater, K., Reddington, S. & Dagnall, N., 10 Jun 2020, In: BMC Family Practice. 21, 8 p., 105.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  1 Citation (Scopus)

• Predicting human intestinal absorption in the presence of bile salt with micellar liquid chromatography

  Waters, L. J., Shokry, D. S. & Parkes, G. M. B., 1 Oct 2016, In: Biomedical Chromatography. 30, 10, p. 1618-1624 7 p.

  Research output: Contribution to journal › Article › peer-review
  11 Citations (Scopus)

• Predicting intention to uptake H1N1 influenza vaccine in a university sample

  Byrne, C., Walsh, J., Kola, S. & Sarma, K. M., 1 Sep 2012, In: British Journal of Health Psychology. 17, 3, p. 582-595 14 p.

  Research output: Contribution to journal › Article › peer-review
  12 Citations (Scopus)

• Predicting Lift-Off Time When Deep-Frying Potato Dough Snacks

  Babb, T., Benham, G. P., Bows, J., Gonzalez-Farina, R., Kiradjiev, K. B., Lee, W. & Tibos, S., 26 Apr 2021, In: SIAM Journal on Applied Mathematics. 81, 2, p. 574-590 17 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  1 Citation (Scopus)

• Predicting Oil Film performance in a Journal Bearing based on Modulation Signal Bispectrum analysis of Vibration Signals

  Hassin, O., Yao, A., Zhang, H. C., Gu, F. & Ball, A., 1 Jul 2017, In: International Journal of COMADEM. 20, 3, p. 19-24 6 p.

  Research output: Contribution to journal › Article › peer-review
  2 Citations (Scopus)

• Predicting Oncotype DX Recurrence Scores using locally available immunohistochemical markers: Experience in a District General Hospital

  Humphris, K., Stephenson, J. & Kumaraswamy, V., 1 Apr 2023, In: Journal of Clinical Pathology. 76, 4, p. 252-255 4 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

• Predicting particle accelerator failures using binary classifiers

  Rescic, M., Seviour, R. & Blokland, W., 1 Mar 2020, In: Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 955, 8 p., 163240.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  18 Citations (Scopus)

• Predicting P-Glycoprotein Effects on Oral Absorption: Correlation of Transport in Caco-2 with Drug Pharmacokinetics in Wild-Type and mdr1a(-/-) Mice in Vivo

  Collett, A., Tanianis-Hughes, J., Hallifax, D. & Warhurst, G., May 2004, In: Pharmaceutical Research. 21, 5, p. 819-826 8 p.

  Research output: Contribution to journal › Article › peer-review
  61 Citations (Scopus)

• Predicting phishing websites based on self-structuring neural network

  Mohammad, R. M., Thabtah, F. & McCluskey, L., 21 Nov 2013, In: Neural Computing and Applications. 25, 2, p. 443-458 16 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  215 Citations (Scopus)

• Predicting plastic deformation and work hardening during V-band formation

  Muller, M., Barrans, S. M. & Blunt, L., 1 Apr 2011, In: Journal of Materials Processing Technology. 211, 4, p. 627-636 10 p.

  Research output: Contribution to journal › Article › peer-review
  21 Citations (Scopus)

• Predicting Post-Discharge Community Violence in England and Wales Using the HCR-20^V3

  Doyle, M., Power, L. A., Coid, J., Kallis, C., Ullrich, S. & Shaw, J., 1 Apr 2014, In: International Journal of Forensic Mental Health. 13, 2, p. 140-147 8 p.

  Research output: Contribution to journal › Article › peer-review
  36 Citations (Scopus)

• Predicting skin permeability using HuskinDB

  Waters, L. & Quah, X. L., 23 Sep 2022, In: Scientific data. 9, 1, 6 p., 584.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  4 Citations (Scopus)

• Predicting stock market performance: The influence of gender and personality on financial decision making

  Plieger, T., Grünhage, T., Duke, É. & Reuter, M., 1 Apr 2021, In: Journal of Individual Differences. 42, 2, p. 64-73 10 p.

  Research output: Contribution to journal › Article › peer-review
  5 Citations (Scopus)

• Predicting supply chain risks using machine learning: The trade-off between performance and interpretability

  Baryannis, G., Dani, S. & Antoniou, G., 1 Dec 2019, In: Future Generation Computer Systems. 101, p. 993-1004 12 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  115 Citations (Scopus)

• Predicting the Dynamic Response of Dual-Rotor System Subject to Interval Parametric Uncertainties Based on the Non-Intrusive Metamodel

  Fu, C., Feng, G., Ma, J., Lu, K., Yang, Y. & Gu, F., 7 May 2020, In: Mathematics. 8, 5, 15 p., 736.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  18 Citations (Scopus)

• Predicting the gastrointestinal behaviour of modified-release products: Utility of a novel dynamic dissolution test apparatus involving the use of bicarbonate buffers

  Merchant, H., Goyanes, A., Parashar, N. & Basit, A. W., 20 Nov 2014, In: International Journal of Pharmaceutics. 475, 1-2, p. 585-591 7 p.

  Research output: Contribution to journal › Article › peer-review
  42 Citations (Scopus)

• Predicting the suitability of microwave formulation using microwave differential thermal analysis (MWDTA)

  Waters, L. J., Ahmad, S. A. & Parkes, G. M. B., 1 Jan 2020, In: Journal of Thermal Analysis and Calorimetry. 139, 1, p. 383-392 10 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

• Predicting tumor responses to mitomycin C on the basis of DT-diaphorase activity or drug metabolism by tumor homogenates: implications for enzyme-directed bioreductive drug development

  Phillips, R. M., Burger, A. M., Loadman, P. M., Jarrett, C. M., Swaine, D. J. & Fiebig, H-H., 15 Nov 2000, In: Cancer Research. 60, 22, p. 6384-90 7 p.

  Research output: Contribution to journal › Article › peer-review
  35 Citations (Scopus)

• Predicting visual outcomes in patients treated with aflibercept for neovascular age-related macular degeneration: Data from a real-world clinical setting

  Fulcher, C., Hazel, C. A., Pacey, I., Ali, H. & Ghanchi, F. D., 1 May 2020, In: European Journal of Ophthalmology. 30, 3, p. 543–549 7 p.

  Research output: Contribution to journal › Article › peer-review
  8 Citations (Scopus)

• Prediction and analysis of engine friction power of a diesel engine influenced by engine speed, load, and lubricant viscosity

  Singh, D., Gu, F., Fieldhouse, J. D., Singh, N. & Singal, S. K., 9 Dec 2014, In: Advances in Tribology. 2014, 10 p., 928015.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  14 Citations (Scopus)

• Prediction models for density and viscosity of biodiesel and their effects on fuel supply system in CI engines

  Tesfa, B., Mishra, R., Gu, F. & Powles, N., Dec 2010, In: Renewable Energy. 35, 12, p. 2752-2760 9 p.

  Research output: Contribution to journal › Article › peer-review
  163 Citations (Scopus)

• Prediction of antilock braking system condition with the vehicle stationary using a model-based approach

  Shi, Z., Legate, I., Gu, F., Fieldhouse, J. & Ball, A., Jun 2010, In: International Journal of Automotive Technology. 11, 3, p. 363-373 11 p.

  Research output: Contribution to journal › Article › peer-review
  2 Citations (Scopus)

• Prediction of diabetes prescription volumes of various geographies using regression techniques

  Mistry, P., 24 Jan 2023, (E-pub ahead of print) In: Health Informatics Journal. 29, 1, 21 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

• Prediction of drug-related problems in diabetic outpatients in a number of hospitals, using a modeling approach

  Al-Taani, G. M., Al-Azzam, S. I., Alzoubi, K. H., Elhajji, F. W. D., Scott, M. G., Alfahel, H. & Aldeyab, M. A., 28 Jul 2017, In: Drug, Healthcare and Patient Safety. 9, p. 65-70 6 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  15 Citations (Scopus)

• Prediction of entrained droplet fraction in co-current annular gas–liquid flow in vertical pipes

  Aliyu, A. M., Almabrok, A. A., Baba, Y. D., Archibong, A. E., Lao, L., Yeung, H. & Kim, K. C., 1 Jul 2017, In: Experimental Thermal and Fluid Science. 85, p. 287-304 18 p.

  Research output: Contribution to journal › Article › peer-review
  33 Citations (Scopus)

• Prediction of human intestinal absorption using micellar liquid chromatography with an aminopropyl stationary phase

  Shokry, D. S., Waters, L. J., Parkes, G. M. B. & Mitchell, J. C., 1 Jul 2019, In: Biomedical Chromatography. 33, 7, 8 p., e4515.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  6 Citations (Scopus)

• Prediction of Low-Back Trouble Frequency in a Working Population

  Burton, A. K., Tillotson, K. M. & Troup, J. D. G., 1 Sep 1989, In: Spine. 14, 9, p. 939-946 8 p.

  Research output: Contribution to journal › Article › peer-review
  64 Citations (Scopus)

• Prediction of mechanical properties of rail pads under in-service conditions through machine learning algorithms

  Ferreño, D., Sainz-Aja, J. A., Carrascal, I. A., Cuartas, M., Pombo, J., Casado, J. A. & Diego, S., 1 Jan 2021, In: Advances in Engineering Software. 151, 11 p., 102927.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  21 Citations (Scopus)

• Prediction of Pressure Gradient in Two and Three-Phase Flows in Vertical Pipes Using an Artificial Neural Network Model

  Ribeiro, J. X. F., Liao, R., Aliyu, A. M. & Liu, Z., 1 Jul 2019, In: International Journal of Engineering and Technology Innovation. 9, 3, p. 155-170 16 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  12 Citations (Scopus)

• Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

  Fergus, P., Cheung, P., Hussain, A., Al-jumeily, D., Dobbins, C., Iram, S. & Wei, Z. (ed.), 28 Oct 2013, In: PLoS One. 8, 10, 16 p., e77154.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  129 Citations (Scopus)

• Prediction of rail corrugation using a rotating flexible wheelset coupled with a flexible track model and a non-Hertzian/non-steady contact model

  Baeza, L., Vila, P., Xie, G. & Iwnicki, S. D., 29 Aug 2011, In: Journal of Sound and Vibration. 330, 18-19, p. 4493-4507 15 p.

  Research output: Contribution to journal › Article › peer-review
  65 Citations (Scopus)

• Prediction of rail damage using a combination of Shakedown Map and wheel-rail contact energy

  Boyacioglu, P. & Bevan, A., 15 Nov 2020, In: Wear. 460-461, 15 p., 203457.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  13 Citations (Scopus)

• Prediction of slab track settlement using an innovative 3D train-track numerical tool: Full-Scale laboratory validation

  Matias, S. R., Ferreira, P. A., Sainz-Aja, J. A. & Pombo, J., 8 Dec 2023, In: Construction and Building Materials. 408, 7 p., 133438.

  Research output: Contribution to journal › Article › peer-review

  Open Access

• Prediction of Surface Topography at the End of Sliding Running-In Wear Based on Areal Surface Parameters

  Lu, W., Zhang, G., Liu, X., Zhou, L., Chen, L. & Jiang, X., 1 May 2014, In: Tribology Transactions. 57, 3, p. 553-560 8 p.

  Research output: Contribution to journal › Article › peer-review
  26 Citations (Scopus)

• Prediction of the Clinical Course of Low-Back Trouble Using Multivariable Models

  Burton, A. K. & Tillotson, K. M., 1 Jan 1991, In: Spine. 16, 1, p. 7-14 8 p.

  Research output: Contribution to journal › Article › peer-review
  49 Citations (Scopus)

• Prediction of the effect of formulation on the toxicity of chemicals

  Mistry, P., Neagu, D., Sanchez-Ruiz, A., Trundle, P. R., Vessey, J. D. & Gosling, J. P., 1 Jan 2017, In: Toxicology Research. 6, 1, p. 42-53 12 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  1 Citation (Scopus)

• Prediction of track settlement at high-speed railway transitions between embankment and bridge in the proximity of a turnout

  Grossoni, I., Hawksbee, S., Jorge, P., Bezin, Y. & Magalhaes, H., 1 Nov 2022, In: Transportation Geotechnics. 37, 16 p., 100879.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  2 Citations (Scopus)

• Prediction of wheel and rail wear under different contact conditions using artificial neural networks

  Shebani, A. & Iwnicki, S., 15 Jul 2018, In: Wear. 406-407, p. 173-184 12 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  97 Citations (Scopus)