AIMC Topic: Machine Learning

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Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction.

Scientific data
The immune response to major trauma has been analysed mainly within post-hospital admission settings where the inflammatory response is already underway and the early drivers of clinical outcome cannot be readily determined. Thus, there is a need to ...

EEG-based image classification via a region-level stacked bi-directional deep learning framework.

BMC medical informatics and decision making
BACKGROUND: As a physiological signal, EEG data cannot be subjectively changed or hidden. Compared with other physiological signals, EEG signals are directly related to human cortical activities with excellent temporal resolution. After the rapid dev...

An Interactive Model of Target and Context for Aspect-Level Sentiment Classification.

Computational intelligence and neuroscience
Aspect-level sentiment classification aims to identify the sentiment polarity of a review expressed toward a target. In recent years, neural network-based methods have achieved success in aspect-level sentiment classification, and these methods fall ...

Ghost hunting in the nonlinear dynamic machine.

PloS one
Integrating dynamic systems modeling and machine learning generates an exploratory nonlinear solution for analyzing dynamical systems-based data. Applying dynamical systems theory to the machine learning solution further provides a pathway to interpr...

Detecting antimicrobial peptides by exploring the mutual information of their sequences.

Journal of biomolecular structure & dynamics
The rise of antibiotic resistance in pathogenic bacteria is a growing concern for every part of the world. The present study shows the prediction efficiency of mutual information for the classification of antimicrobial peptides. The proven role of an...

Application of automated electron microscopy imaging and machine learning to characterise and quantify nanoparticle dispersion in aqueous media.

Journal of microscopy
For many nanoparticle applications it is important to understand dispersion in liquids. For nanomedicinal and nanotoxicological research this is complicated by the often complex nature of the biological dispersant and ultimately this leads to severe ...

Estimate ecotoxicity characterization factors for chemicals in life cycle assessment using machine learning models.

Environment international
In life cycle assessment, characterization factors are used to convert the amount of the chemicals and other pollutants generated in a product's life cycle to the standard unit of an impact category, such as ecotoxicity. However, as a widely used imp...

Point-of-Care Serodiagnostic Test for Early-Stage Lyme Disease Using a Multiplexed Paper-Based Immunoassay and Machine Learning.

ACS nano
Caused by the tick-borne spirochete , Lyme disease (LD) is the most common vector-borne infectious disease in North America and Europe. Though timely diagnosis and treatment are effective in preventing disease progression, current tests are insensiti...

Latest trends in structure based drug design with protein targets.

Advances in protein chemistry and structural biology
Structure based drug designing is an important endeavor in the field of structural bioinformatics. Previously the entire process was dependent on the wet-lab experiments to build libraries of ligand molecules. And the molecules used to be tested to d...