AI Medical Compendium Topic:
Models, Statistical

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Construction of longitudinal prediction targets using semisupervised learning.

Statistical methods in medical research
In establishing prognostic models, often aided by machine learning methods, much effort is concentrated in identifying good predictors. However, the same level of rigor is often absent in improving the outcome side of the models. In this study, we fo...

Enumerateblood - an R package to estimate the cellular composition of whole blood from Affymetrix Gene ST gene expression profiles.

BMC genomics
BACKGROUND: Measuring genome-wide changes in transcript abundance in circulating peripheral whole blood is a useful way to study disease pathobiology and may help elucidate the molecular mechanisms of disease, or discovery of useful disease biomarker...

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

PloS one
BACKGROUND: The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate predic...

Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

PloS one
Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfe...

Intelligent Noninvasive Diagnosis of Aneuploidy: Raw Values and Highly Imbalanced Dataset.

IEEE journal of biomedical and health informatics
The objective of this paper is to introduce a noninvasive diagnosis procedure for aneuploidy and to minimize the social and financial cost of prenatal diagnosis tests that are performed for fetal aneuploidies in an early stage of pregnancy. We propos...

Grouping miRNAs of similar functions via weighted information content of gene ontology.

BMC bioinformatics
BACKGROUND: Regulation mechanisms between miRNAs and genes are complicated. To accomplish a biological function, a miRNA may regulate multiple target genes, and similarly a target gene may be regulated by multiple miRNAs. Wet-lab knowledge of co-regu...

A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data.

BMC genomics
BACKGROUND: The ability to sequence the transcriptomes of single cells using single-cell RNA-seq sequencing technologies presents a shift in the scientific paradigm where scientists, now, are able to concurrently investigate the complex biology of a ...

Comparison of Classifier Architectures for Online Neural Spike Sorting.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce...