AIMC Topic: Models, Statistical

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Machine learning for radiation outcome modeling and prediction.

Medical physics
AIMS: This review paper intends to summarize the application of machine learning to radiotherapy outcome modeling based on structured and un-structured radiation oncology datasets.

Making Sense of Computational Psychiatry.

The international journal of neuropsychopharmacology
In psychiatry we often speak of constructing "models." Here we try to make sense of what such a claim might mean, starting with the most fundamental question: "What is (and isn't) a model?" We then discuss, in a concrete measurable sense, what it mea...

Intelligent-assistant system for scleral spur location.

Applied optics
A system based on the use of two artificial neural networks (ANNs) to determine the location of the scleral spur of the human eye in ocular images generated by an ultrasound biomicroscopy is presented in this paper. The two ANNs establish a relations...

Machine learning in the estimation of causal effects: targeted minimum loss-based estimation and double/debiased machine learning.

Biostatistics (Oxford, England)
In recent decades, the fields of statistical and machine learning have seen a revolution in the development of data-adaptive regression methods that have optimal performance under flexible, sometimes minimal, assumptions on the true regression functi...

Natural language processing for structuring clinical text data on depression using UK-CRIS.

Evidence-based mental health
BACKGROUND: Utilisation of routinely collected electronic health records from secondary care offers unprecedented possibilities for medical science research but can also present difficulties. One key issue is that medical information is presented as ...

Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach.

IET systems biology
The major intent of peptide vaccine designs, immunodiagnosis and antibody productions is to accurately identify linear B-cell epitopes. The determination of epitopes through experimental analysis is highly expensive. Therefore, it is desirable to dev...

Using a simple open-source automated machine learning algorithm to forecast COVID-19 spread: A modelling study.

Advances in respiratory medicine
INTRODUCTION: Machine learning algorithms have been used to develop prediction models in various infectious and non-infectious settings including interpretation of images in predicting the outcome of diseases. We demonstrate the application of one su...

EHAI: Enhanced Human Microbe-Disease Association Identification.

Current protein & peptide science
Recently, an increasing number of biological and clinical reports have demonstrated that imbalance of microbial community has the ability to play important roles among several complex diseases concerning human health. Having a good knowledge of disco...