AIMC Topic: Machine Learning

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Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles.

BioMed research international
. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous chall...

Detecting negation and scope in Chinese clinical notes using character and word embedding.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Researchers have developed effective methods to index free-text clinical notes into structured database, in which negation detection is a critical but challenging step. In Chinese clinical records, negation detection is par...

Quantifying Risk for Anxiety Disorders in Preschool Children: A Machine Learning Approach.

PloS one
Early childhood anxiety disorders are common, impairing, and predictive of anxiety and mood disorders later in childhood. Epidemiological studies over the last decade find that the prevalence of impairing anxiety disorders in preschool children range...

Integration of metabolomics, lipidomics and clinical data using a machine learning method.

BMC bioinformatics
BACKGROUND: The recent pandemic of obesity and the metabolic syndrome (MetS) has led to the realisation that new drug targets are needed to either reduce obesity or the subsequent pathophysiological consequences associated with excess weight gain. Ce...

An intelligent prognostic system for analyzing patients with paraquat poisoning using arterial blood gas indexes.

Journal of pharmacological and toxicological methods
The arterial blood gas (ABG) test is used to assess gas exchange in the lung, and the acid-base level in the blood. However, it is still unclear whether or not ABG test indexes correlate with paraquat (PQ) poisoning. This study investigates the predi...

An information-based machine learning approach to elasticity imaging.

Biomechanics and modeling in mechanobiology
An information-based technique is described for applications in mechanical property imaging of soft biological media under quasi-static loads. We adapted the Autoprogressive method that was originally developed for civil engineering applications for ...

Applications of Spectral Gradient Algorithm for Solving Matrix ℓ2,1-Norm Minimization Problems in Machine Learning.

PloS one
The main purpose of this study is to propose, then analyze, and later test a spectral gradient algorithm for solving a convex minimization problem. The considered problem covers the matrix ℓ2,1-norm regularized least squares which is widely used in m...

DCAN: Deep contour-aware networks for object instance segmentation from histology images.

Medical image analysis
In histopathological image analysis, the morphology of histological structures, such as glands and nuclei, has been routinely adopted by pathologists to assess the malignancy degree of adenocarcinomas. Accurate detection and segmentation of these obj...

Classification of Porcine Cranial Fracture Patterns Using a Fracture Printing Interface.

Journal of forensic sciences
Distinguishing between accidental and abusive head trauma in children can be difficult, as there is a lack of baseline data for pediatric cranial fracture patterns. A porcine head model has recently been developed and utilized in a series of studies ...