AIMC Topic: Machine Learning

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Semi-automated prediction approach of target shifts using machine learning with anatomical features between planning and pretreatment CT images in prostate radiotherapy.

Journal of radiation research
The goal of this study was to develop a semi-automated prediction approach of target shifts using machine learning architecture (MLA) with anatomical features for prostate radiotherapy. Our hypothesis was that anatomical features between planning com...

Graph- and rule-based learning algorithms: a comprehensive review of their applications for cancer type classification and prognosis using genomic data.

Briefings in bioinformatics
Cancer is well recognized as a complex disease with dysregulated molecular networks or modules. Graph- and rule-based analytics have been applied extensively for cancer classification as well as prognosis using large genomic and other data over the p...

Investigating the role of Simpson's paradox in the analysis of top-ranked features in high-dimensional bioinformatics datasets.

Briefings in bioinformatics
An important problem in bioinformatics consists of identifying the most important features (or predictors), among a large number of features in a given classification dataset. This problem is often addressed by using a machine learning-based feature ...

Machine learning in nephrology: scratching the surface.

Chinese medical journal
Machine learning shows enormous potential in facilitating decision-making regarding kidney diseases. With the development of data preservation and processing, as well as the advancement of machine learning algorithms, machine learning is expected to ...

Machine Learning Uncovers Food- and Excipient-Drug Interactions.

Cell reports
Inactive ingredients and generally recognized as safe compounds are regarded by the US Food and Drug Administration (FDA) as benign for human consumption within specified dose ranges, but a growing body of research has revealed that many inactive ing...

A Machine-Learning Approach to Predicting Smoking Cessation Treatment Outcomes.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
AIMS: Most cigarette smokers want to quit smoking and more than half make an attempt every year, but less than 10% remain abstinent for at least 6 months. Evidence-based tobacco use treatment improves the likelihood of quitting, but more than two-thi...

Geometry of Energy Landscapes and the Optimizability of Deep Neural Networks.

Physical review letters
Deep neural networks are workhorse models in machine learning with multiple layers of nonlinear functions composed in series. Their loss function is highly nonconvex, yet empirically even gradient descent minimization is sufficient to arrive at accur...