Results 221 to 230 of about 874,956 (269)

A Simple Framework for Collaborative Development of Predictive Models Trained on Proprietary Data. [PDF]

J Chem Inf Model
Rodríguez-Belenguer P, Amberg A, Bringezu F, Frericks M, Hemmerich J, Monecke P, Oberhauser N, Trairatphisan P, Pastor M.   +8 more
europepmc   +1 more source

Development and validation of predictive models for SIRS and severe hemorrhage following percutaneous nephrolithotomy: the role of hydronephrosis and inter-correlation. [PDF]

BMC Surg
Wan W, Yang J, Yuan D, Wang Y, Wang B, Wu W, Yu X.   +6 more
europepmc   +1 more source

The multi-dimensional equity of predictive models in acute ischaemic stroke

Rondina JM, Giles D, Foulon C, Wright P, Pombo G, Ruffle J, Ourselin S, Cardoso J, Rees G, Nachev P.   +9 more
europepmc   +1 more source

AI-Powered Predictive Models in Implant Dentistry: Planning, Risk Assessment, and Outcomes. [PDF]

J Clin Med
Neji G, Gasparro R, Tlili M, Dhahri A, Khanfir F, Sammartino G, Aliberti A, Campana MD, Ben Amor F.   +8 more
europepmc   +1 more source

High resolution temperature forecasting using functional time series decomposition and advanced predictive models. [PDF]

Sci Rep
Alshanbari HM, Aldhabani MS, Iqbal N, Saeed AM, Noori N.   +4 more
europepmc   +1 more source

Registered report: Stress testing predictive models of ideological prejudice. [PDF]

PLoS One
Thompson JL, Cassario AL, Vallabha S, Gnall SA, Rice S, Solanki P, Carrillo A, Brandt MJ, Wetherell GA.   +8 more
europepmc   +1 more source

Evaluating scientific theories as predictive models in language neuroscience

Singh C, Antonello RJ, Guo S, Mischler G, Gao J, Mesgarani N, Huth AG.   +6 more
europepmc   +1 more source

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Multilevel Model Prediction

Psychometrika, 2006
Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling—model disturbances, random coefficients, and future response ...
Frees, Edward W., Kim, Jee-Seon
openaire   +1 more source

Nomograms as predictive models

Seminars in Urologic Oncology, 2002
Nomograms are valuable tools for estimating the likelihood of cancer being diagnosed, the pathologic features of a localized cancer, and the prognosis of a patient after treatment. Although the available nomograms are reasonably accurate, better predictive factors including additional clinical factors and new molecular analyses are needed to improve ...
James A, Eastham, Michael W, Kattan, Peter T, Scardino   +2 more
openaire   +2 more sources