AIMC Topic: Machine Learning

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Comparison of Machine Learning Techniques for Mortality Prediction in a Prospective Cohort of Older Adults.

International journal of environmental research and public health
As global demographics change, ageing is a global phenomenon which is increasingly of interest in our modern and rapidly changing society. Thus, the application of proper prognostic indices in clinical decisions regarding mortality prediction has ass...

UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning.

International journal of molecular sciences
Umami ingredients have been identified as important factors in food seasoning and production. Traditional experimental methods for characterizing peptides exhibiting umami sensory properties (umami peptides) are time-consuming, laborious, and costly....

Machine learning modeling of genome-wide copy number alteration signatures reliably predicts IDH mutational status in adult diffuse glioma.

Acta neuropathologica communications
Knowledge of 1p/19q-codeletion and IDH1/2 mutational status is necessary to interpret any investigational study of diffuse gliomas in the modern era. While DNA sequencing is the gold standard for determining IDH mutational status, genome-wide methyla...

A weakly supervised model for the automated detection of adverse events using clinical notes.

Journal of biomedical informatics
With clinical trials unable to detect all potential adverse reactions to drugs and medical devices prior to their release into the market, accurate post-market surveillance is critical to ensure their safety and efficacy. Electronic health records (E...

Energy Consumption Forecasting for Smart Meters Using Extreme Learning Machine Ensemble.

Sensors (Basel, Switzerland)
The employment of smart meters for energy consumption monitoring is essential for planning and management of power generation systems. In this context, forecasting energy consumption is a valuable asset for decision making, since it can improve the p...

Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative Study.

Sensors (Basel, Switzerland)
Efficiently implementing remote sensing image classification with high spatial resolution imagery can provide significant value in land use and land cover (LULC) classification. The new advances in remote sensing and deep learning technologies have f...

A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets.

PLoS computational biology
Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and...

Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods.

Computational and mathematical methods in medicine
Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health cris...

Increasing efficiency and accuracy of magnetic interaction calculations in colloidal simulation through machine learning.

Journal of colloid and interface science
Calculating the magnetic interaction between magnetic particles that are positioned in close proximity to one another is a surprisingly challenging task. Exact solutions for this interaction exist either through numerical expansion of multipolar inte...