Results 281 to 290 of about 1,728,519 (315)

Development of a machine learning-based mortality prediction model for patients with mental disorders and COVID-19. [PDF]

Front Cell Infect Microbiol
Zhang Y, Wang H, Yang M, Cui Z, Wang J, Qian G, Li S, Luo H, Zhang S, Wang L, Zhang D, Li G, Hu X, Bai Q, Ren Z.   +14 more
europepmc   +1 more source

MicroRNA target gene prediction model based on input-feature dependency and sample data expansion technique. [PDF]

PLoS Comput Biol
Shao Y, Li Y, Zhai H, Dong S.
europepmc   +1 more source

Development and validation of a prediction model for cardiovascular-kidney-metabolic syndrome progression: a multicenter study. [PDF]

Front Nutr
Tu J, Chen F, Yan W, Xu Z, Zhan Y, Yang X.   +5 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

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

Structure prediction and modelling

Current Opinion in Biotechnology, 1991
Protein structure prediction from sequence remains a major goal in molecular biology. The methods described in this review concentrate on deriving structural information through the detection of similarities between a test sequence and a database of known structures. Such methods are often referred to as knowledge-based strategies reflecting the use of
M B, Swindells, J M, Thornton
openaire   +2 more sources

MODEL IMPERFECTION AND PREDICTING PREDICTABILITY

International Journal of Bifurcation and Chaos, 2013
It has been argued that Lyapunov exponents as a measure of predictability are of limited value because they only provide a global average. Characterizing an attractor by a distribution of times for initial uncertainties to increase by a factor of q has been suggested as a more useful alternative.
openaire   +1 more source

Predictive Models in Urology

Urologia Journal, 2013
Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of ...
openaire   +2 more sources