AIMC Topic: Models, Statistical

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Conceptualization in reference production: Probabilistic modeling and experimental testing.

Psychological review
In psycholinguistics, there has been relatively little work investigating conceptualization-how speakers decide which concepts to express. This contrasts with work in natural language generation (NLG), a subfield of artificial intelligence, where muc...

Decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) models for sediment transport in sewer pipes.

Water science and technology : a journal of the International Association on Water Pollution Research
Sediment deposition in sewers and urban drainage systems has great effect on the hydraulic capacity of the channel. In this respect, the self-cleansing concept has been widely used for sewers and urban drainage systems design. This study investigates...

Causal models adjusting for time-varying confounding-a systematic review of the literature.

International journal of epidemiology
BACKGROUND: Obtaining unbiased causal estimates from longitudinal observational data can be difficult due to exposure-affected time-varying confounding. The past decade has seen considerable development in methods for analysing such complex longitudi...

Facilitating prediction of adverse drug reactions by using knowledge graphs and multi-label learning models.

Briefings in bioinformatics
Timely identification of adverse drug reactions (ADRs) is highly important in the domains of public health and pharmacology. Early discovery of potential ADRs can limit their effect on patient lives and also make drug development pipelines more robus...

Predictive analysis across spatial scales links zoonotic malaria to deforestation.

Proceedings. Biological sciences
The complex transmission ecologies of vector-borne and zoonotic diseases pose challenges to their control, especially in changing landscapes. Human incidence of zoonotic malaria ( Plasmodium knowlesi) is associated with deforestation although mechani...

Machine Learning to Predict Binding Affinity.

Methods in molecular biology (Clifton, N.J.)
Recent progress in the development of scientific libraries with machine-learning techniques paved the way for the implementation of integrated computational tools to predict ligand-binding affinity. The prediction of binding affinity uses the atomic ...

Real-time Epidemic Forecasting: Challenges and Opportunities.

Health security
Infectious disease outbreaks play an important role in global morbidity and mortality. Real-time epidemic forecasting provides an opportunity to predict geographic disease spread as well as case counts to better inform public health interventions whe...

Results of a Literature Review to Prepare Data Modelling in the Context of Kidney Transplant Rejection Diagnosis.

Studies in health technology and informatics
Due to demographic change the number of serious kidney diseases and thus required transplantations will increase. The increased demand for donor organs and a decreasing supply of these organs underline the necessity for effective early rejection diag...

Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Accurately estimating performance accuracy of machine learning classifiers is of fundamental importance in biomedical research with potentially societal consequences upon the deployment of bestperforming tools in everyday life. Although classificatio...

Machine learning in multiexposure laser speckle contrast imaging can replace conventional laser Doppler flowmetry.

Journal of biomedical optics
Laser speckle contrast imaging (LSCI) enables video rate imaging of blood flow. However, its relation to tissue blood perfusion is nonlinear and depends strongly on exposure time. By contrast, the perfusion estimate from the slower laser Doppler flow...