prediction models given a user's input of model discrimination (AUC) - the process to transform the AUC to a Cohen's D value is proposed here http://dx.doi.org/10.5093/ejpalc2018a5 and we have a journal article currently under review which uses it for the same purpose as in this ...
Set the status property: Prediction model life cycle. When prediction is in PendingModelConfirmation status, it is allowed to update the status to PendingFeaturing or Active through API. Parameters: status - the status value to set. Returns: the PredictionModelStatusInner obje...
Both in-hospital cardiac arrest (IHCA) and out-of-hospital cardiac arrest (OHCA) have higher incidence and lower survival rates. Predictors of in-hospital mortality for intensive care unit (ICU) admitted cardiac arrest (CA) patients remain unclear. The M
Of our eight new tools, we recommend using LDAK-Bolt-Predict when analyzing individual-level data, and LDAK-BayesR-SS when analyzing summary statistics (in both cases, we advise using the tools assuming the BLD-LDAK Model). When using LDAK-Bolt-Predict, the average increase in R2 due ...
Building on these two challenges, this paper establishes a real-time ROP prediction model based on the GRU-Informer. Related work ROP prediction The development of mechanical drilling speed prediction has gone through several stages, encompassing various methods and technologies. In the early stages ...
In this work, we proposed a real-time prediction model for carbon content in molten steel using real-time operation data and the carbon oxide content in off-gas and showed that the decarburization end time could be accurately determined using the model. The main idea of this study is that ...
A novel hybrid model is proposed to improve the accuracy of ultra-short-term wind speed prediction by combining the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), the sample entropy (SE), optimized recurrent broad
If you use a different gene model, please make sure to filter GTF file and select a representative transcript for each gene before running the pipeline. The input data for the transcript-level model was created based onhttps://storage.googleapis.com/gtex_analysis_v7/reference/gencode.v19.transc...
For hourly PM2.5 concentration prediction, it is beneficial to split the whole dataset into several subsets with similar properties and to train a local prediction model for each subset. However, the methods based on local models need to solve the global-local duality. In this study, a novel ...
Finally, we excluded all variants in \(SwissProt_{gnomAD}\) located on genes that appear in ClinVarTraining and defined it as an orthogonal validation set. MAGPIE framework The machine learning component of MAGPIE is based on a gradient-boosting tree-based model of classifying pathogenic and ...