AI Medical Compendium Topic:
Models, Statistical

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A Hybrid Neural Network Model for Sales Forecasting Based on ARIMA and Search Popularity of Article Titles.

Computational intelligence and neuroscience
Enhancing sales and operations planning through forecasting analysis and business intelligence is demanded in many industries and enterprises. Publishing industries usually pick attractive titles and headlines for their stories to increase sales, sin...

Representing higher-order dependencies in networks.

Science advances
To ensure the correctness of network analysis methods, the network (as the input) has to be a sufficiently accurate representation of the underlying data. However, when representing sequential data from complex systems, such as global shipping traffi...

Learning statistical models of phenotypes using noisy labeled training data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Traditionally, patient groups with a phenotype are selected through rule-based definitions whose creation and validation are time-consuming. Machine learning approaches to electronic phenotyping are limited by the paucity of labeled traini...

Chemical entity recognition in patents by combining dictionary-based and statistical approaches.

Database : the journal of biological databases and curation
We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Pa...

A hierarchical model for integrating unsupervised generative embedding and empirical Bayes.

Journal of neuroscience methods
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based c...

Using ELM-based weighted probabilistic model in the classification of synchronous EEG BCI.

Medical & biological engineering & computing
Extreme learning machine (ELM) is an effective machine learning technique with simple theory and fast implementation, which has gained increasing interest from various research fields recently. A new method that combines ELM with probabilistic model ...

Flexible variable selection for recovering sparsity in nonadditive nonparametric models.

Biometrics
Variable selection for recovering sparsity in nonadditive and nonparametric models with high-dimensional variables has been challenging. This problem becomes even more difficult due to complications in modeling unknown interaction terms among high-di...

The Virtual Screening of the Drug Protein with a Few Crystal Structures Based on the Adaboost-SVM.

Computational and mathematical methods in medicine
Using the theory of machine learning to assist the virtual screening (VS) has been an effective plan. However, the quality of the training set may reduce because of mixing with the wrong docking poses and it will affect the screening efficiencies. To...

Prediction and detection models for acute kidney injury in hospitalized older adults.

BMC medical informatics and decision making
BACKGROUND: Acute Kidney Injury (AKI) occurs in at least 5 % of hospitalized patients and can result in 40-70 % morbidity and mortality. Even following recovery, many subjects may experience progressive deterioration of renal function. The heterogene...

Diabetic peripheral neuropathy class prediction by multicategory support vector machine model: a cross-sectional study.

Epidemiology and health
OBJECTIVES: Diabetes is increasing in worldwide prevalence, toward epidemic levels. Diabetic neuropathy, one of the most common complications of diabetes mellitus, is a serious condition that can lead to amputation. This study used a multicategory su...