Predicting periprosthetic joint infection: external validation of preoperative prediction models by S.-J. Yoon, P. C. Jutte, A. Soriano, R. Sousa, W. P. Zijlstra, M. Wouthuyzen-Bakker

“…<p><strong>Introduction</strong>: Prediction models for periprosthetic joint infections (PJIs) are gaining interest due to their potential to improve clinical decision-making. …”
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Development of a deep learning-based model for predicting of dominant seepage channels in oil reservoirs by Chen Liu, Zenghua Zhang, Wensheng Zhou, Chengyu Luo, Lei Jiang

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Modeling and Discovering Direct Causes for Predictive Models by Yizuo Chen, Amit Bhatia

“… We introduce a causal modeling framework that captures the input-output behavior of predictive models (e.g., machine learning models). …”
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Enhancing Agricultural Sustainability Through Intelligent Irrigation Using PVT Energy Applications: Implementing Hybrid Machine and Deep Learning Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…This solution integrates PVT applications, prediction, modelling and forecasting as well as plants’ physiological characteristics. …”
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Control of Electric Drive with Predicting Model by N. N. Micheev, E. P. Ratkevich

“…The proposed predicting model permits to exclude immediate rapid time calculations of a control value.…”
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Statin effects on the lipidome: Predicting statin usage and implications for cardiovascular risk prediction by Changyu Yi, Kevin Huynh, Yvette Schooneveldt, Gavriel Olshansky, Amy Liang, Tingting Wang, Habtamu B. Beyene, Aleksandar Dakic, Jingqin Wu, Michelle Cinel, Natalie A. Mellett, Gerald F. Watts, Joseph Hung, Jennie Hui, John Beilby, Joanne E. Curran, John Blangero, Eric K. Moses, John Simes, Andrew M. Tonkin, Leonard Kritharides, David Sullivan, Jonathan E. Shaw, Dianna J. Magliano, Agus Salim, Corey Giles, Peter J. Meikle, A. Tonkin, P. Aylward, D. Colquhoun, P. Glasziou, P. Harris, D. Hunt, A. Keech, S. MacMahon, P. Magnus, D. Newel, P. Nestel, N. Sharpe, J. Shaw, R.J. Simes, P. Thompson, A. Thomson, M. West, H. White, A. Thomson, S. Simes, D. Colquhoun, W. Hague, S. MacMahon, R.J. Simes, R.J. Simes, P. Glasziou, S. Caleo, J. Hall, A. Martin, S. Mulray, P. Barter, L. Beilin, R. Collins, J. McNeil, P. Meier, H. Willimott, P. Harris, W. Hague, D. Smithers, A. Tonkin, P. Wallace, H. Willimott, D. Hunt, J. Baker, P. Aylward, P. Harris, M. Hobbs, P. Thompson, N. Sharpe, D. Hunt, M. West, P. Thompson, H. White, P. Aylward, D. Colquhoun, D. Sullivan, A. Keech, P. Thompson, S. MacMahon, A. Tonkin, M. West, H. White, N. Anderson, G. Hankey, R.J. Simes, S. Simes, J. Watson, R.J. Simes, N. Sharpe, A. Thomson, A. Tonkin, H. White, W. Hague, J. Baker, M. Arulchelvam, S. Chup, J. Daly, J. Hanna, A. Leach, M. Lee, J. Loughhead, H. Lundie-Jenkin, J. Morrison, A. Martin, S. Mulray, S. Netting, A. Nguyen, H. Pater, R. Philip, G. Pinna, D. Rattos, S. Ryerson, V. Sazhin, S. Simes, R. Walsh, A. Keech, R.J. Simes, A. Clague, M. Mackie, J. Yallop, K. Boss, S. MacMahon, M. Whiting, M. Shepard, J. Leach, M. Gandy, J. Joughin, J. Seabrook, R. Abraham, J. Allen, F. Bates, I. Beinart, E. Breed, D. Brown, N. Bunyan, D. Calvert, T. Campbell, D. Condon-Paoloni, B. Conway, L. Coupland, J. Crowe, N. Cunio, B. Cuthbert, N. Cuthbert, S. D’Arcy, P. Davidson, B. Dwyer, J. England, C. Friend, G. Fulcher, S. Grant, K. Hellestrand, M. Kava, L. Kritharides, D. McGill, H. McKee, A. McLean, M. Neaverson, G. Nelson, M. O’Neill, C. Onuma, F. O’Reilly, A. Owensby, D. Owensby, J. Padley, G. Parnell, S. Paterson, C. Pawsey, R. Portley, K. Quinn, D. Ramsay, M. Russell, J. Ryan, B. Sambrook, L. Shields, J. Silberberg, S. Sinclair, D. Sullivan, P. Taverner, D. Taylor, M. Taylor, M. Threlfall, J. Turner, A. Viles, J. Waites, R. Walker, W. Walsh, K. Wee, P. West, R. Wikramanayake, D. Wilcken, J. Woods, R.K. Barnett, Z. Bogetic, H. Briggs, A. Broughton, L. Brown, A. Buncle, P. Calafiore, L. Carrick, Y. Cavenett, L. Champness, R. Clark, H. Connor, J. Counsell, J. Deague, G. Derwent-Smith, A. Driscoll, B. Feldtmann, L. Fisher, B. Forge, A. Hamer, H. Harrap, S. Hodgens, M. Hooten, J. Hurley, B. Jackson, J. Johns, J. Krafchek, H. Larwill, I. Lyall, S. Marks, M. Martin, B. Mason, J. McCabe, C. Medley, L. Morgan, L. Mullan, D. Ogilvy, G. Phelps, P. Phillips, H. Prendergast, D. Rose, G. Rudge, W. Ryan, M. Sallaberger, G. Savige, B. Sia, A. Soward, C. Steinfort, K. Tankard, J. Tippett, B. Tyack, J. Voukelatis, M. Wahlqvist, N. Walker, S. Whitten, R. Yee, M. Zanoni, R. Ziffer, K. Anderson, G. Aroney, C. Atkinson, K. Boyd, R. Bradfield, G. Cameron, D. Careless, A. Carle, P. Carroll, T. Carruthers, D. Chaseling, B. Cooke, S. Coverdale, B. Currie, M. d’Emden, F. Ekin, R. Elder, T. Elsley, L. Ferry, C. Gnanaharan, K. Graham, K. Gunawardane, C. Hadfield, C. Halliday, R. Halliday, A. Heyworth, B. Hicks, P. Hicks, T. Htut, L. Hughes, J. Humphries, H. LeGood, J. Nye, D. O’Brien, G. Real, K. Roberts, L. RossLee, J. Sampson, I. Scott, H. Smith, V. Smith-Orr, Y. Tan, B. Wicks, J. Wicks, S. Woodhouse, J. Bradley, L. Callaway, A. Calvert, J. Crettenden, A. Dufek, B. Dunn, C. Dunphy, D. Gow, I. Hamilton-Craig, K. Herewane, S. Keynes, L. McLeay, R. McLeay, L. Ng, C. Thomas, P. Tideman, L. Wilson, R. Yeend, C. Zhang, Y. Zhang, P. Bradshaw, M. Brooks, R. Burton, J. Garrett, K. Gotch-Martin, J. Hargan, B. Hockings, G. Lane, S. Ross, R. Cutforth, D. D’Silva, W. Hitchener, V. Kimber, G. Kirkland, P. Neid, R. Parkes, B. Singh, C. Singh, M. Smith, S. Smith, M. Templer, N. Whitehouse, R. Allen-Narker, R. Anandaraja, S. Anandaraja, P. Barclay, S. Baskaranathan, P. Bridgman, J. Brown, J. Bruning, J. Calton, A. Clague, M. Clark, D. Clarke, T. Cook, R. Coxon, M. Denton, A. Doone, R. Easthope, J. Elliott, C. Ellis, P. FosterPratt, C. Frenneux, M. Frenneux, D. Friedlander, D. Fry, L. Gibson, M. Gluyas, A. Hall, K. Hall, A. Hamer, H. Hart, P. Healy, J. Hedley, P. Heuser, H. Ikram, D. Jardine, J. Kenyon, H. King, T. Kirk, T. Lawson, P. Leslie, G. Lewis, E. Low, R. Luke, S. Mann, D. McClean, D. McHaffie, L. Nairn, H. Patel, L. Pearce, K. Ramanathan, R. Rankin, J. Reddy, S. Reuben, R. Ronaldson, D. Roy, H. Roy, P. Scobie, D. Scott, J. Scott, K. Skjellerup, R. Stewart, D. Walters, T. Wilkins, A. Vitanachy, P. Wright, A. Zambanini

“…We demonstrated that the re-weighted models achieved comparable prediction accuracy to ad hoc models which use the aligned predictor between training and target data. …”
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Models for Predicting the Probability of Bankruptcy: Applying in Construction Companies by A. V. Voiko

“…It has been also revealed that models for predicting financial insolvency of enterprises has not been able to assess changes in financial stability in the short term. …”
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QSAR Models for Predicting the Antioxidant Potential of Chemical Substances by Sofia Ghironi, Edoardo Luca Viganò, Gianluca Selvestrel, Emilio Benfenati

“…Given these results, we developed an integrated method that not only outperformed the individual models, achieving an R² of 0.78 on the external test set, but also provided valuable insights into the range of predicted values.…”
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Generalizable deep learning models for predicting laboratory earthquakes by Chonglang Wang, Kaiwen Xia, Wei Yao, Chris Marone

“…Abstract Machine learning models can predict laboratory earthquakes using Acoustic emission, the lab equivalent of microseismicity, and changes in fault zone elastic properties during the lab seismic cycle. …”
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Tabular Data Models for Predicting Art Auction Results by Patryk Mauer, Szczepan Paszkiel

“…Additionally, we address the interpretability of models, which is crucial for understanding the influence of various features on predictions. …”
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Predicting Financial Market Volatility with Modern Model and Traditional Model by R. G. Aldeki

“…There is evidence that the GARCH-SVR model performs best for predicting volatility time series, and classical volatility model techniques have an enormous predictive performance better than machine learning models.…”
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Prediction of mortality in very premature infants: a systematic review of prediction models. by Stephanie Medlock, Anita C J Ravelli, Pieter Tamminga, Ben W M Mol, Ameen Abu-Hanna

“…There are validated prediction models for classification and case-mix adjustment. …”
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Review of Models for Estimating and Predicting the Amount of Energy Produced by Solar Energy Systems by Simankov V., Buchatskiy P., Onishchenko S., Teploukhov S.

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Explainable Model Prediction of Memristor by Sruthi Pallathuvalappil, Rahul Kottappuzhackal, Alex James

“…The accurate memristor model prediction becomes critical to decipher the overall circuit function in a wide range of nonideal and practical conditions. …”
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Atmospheric Modeling for Wildfire Prediction by Fathima Nuzla Ismail, Brendon J. Woodford, Sherlock A. Licorish

Subjects: “…one-class machine learning models…”
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Prediction Model for Soybean Productivity by Ion GANEA

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Modelling complexity : The limits to prediction by Michael Batty, Paul M. Torrens

“…We develop these, introducing changes in the meaning of validity posed by the use to which such models are to be put in terms of their users. We draw these ideas together as conclusions about the limits posed to prediction in complex systems. …”
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Evaluating the Accuracy of Land-Use Change Models for Predicting Vegetation Loss Across Brazilian Biomes by Macleidi Varnier, Eliseu José Weber

“…Land-use change models are used to predict future land-use scenarios. …”
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Study on predictive models for COVID-19 in Cuba by Juan Felipe Medina Mendieta, Manuel Eduardo Cortés Cortés, Manuel Cortés Iglesias, Annia del Carmen Pérez Fernández, Marianelis Manzano Cabrera

“…<br /><strong>Results:</strong> there is an adequacy of the presented models with respect to the predicted and the real values which allow their reliability for the predictions made for Cuba.…”
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Risk-Stratified Predictive Models of Pregnancy Loss by O. V. Shirai, B. I. Aslanov, S. V. Rishchuk, S. E. Melnikova

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