AIMC Topic: Machine Learning

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Assessment of Time-Series Machine Learning Methods for Forecasting Hospital Discharge Volume.

JAMA network open
IMPORTANCE: Forecasting the volume of hospital discharges has important implications for resource allocation and represents an opportunity to improve patient safety at periods of elevated risk.

Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses.

Scientific reports
Neurophysiological features like event-related potentials (ERPs) have long been used to identify different cognitive sub-processes that may contribute to task performance. It has however remained unclear whether "classical" ERPs are truly the best re...

LogLoss-BERAF: An ensemble-based machine learning model for constructing highly accurate diagnostic sets of methylation sites accounting for heterogeneity in prostate cancer.

PloS one
Although modern methods of whole genome DNA methylation analysis have a wide range of applications, they are not suitable for clinical diagnostics due to their high cost and complexity and due to the large amount of sample DNA required for the analys...

Learning-Based Quality Control for Cardiac MR Images.

IEEE transactions on medical imaging
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned and on the potential occurrence of imaging artifacts, such as cardiac...

Will machine learning end the viability of radiology as a thriving medical specialty?

The British journal of radiology
There have been tremendous advances in artificial intelligence (AI) and machine learning (ML) within the past decade, especially in the application of deep learning to various challenges. These include advanced competitive games (such as Chess and Go...

Machine-Learning Approach to Optimize SMOTE Ratio in Class Imbalance Dataset for Intrusion Detection.

Computational intelligence and neuroscience
The KDD CUP 1999 intrusion detection dataset was introduced at the third international knowledge discovery and data mining tools competition, and it has been widely used for many studies. The attack types of KDD CUP 1999 dataset are divided into four...

Optimal Synthesis of Four-Bar Linkage Path Generation through Evolutionary Computation with a Novel Constraint Handling Technique.

Computational intelligence and neuroscience
This paper presents a novel constraint handling technique for optimum path generation of four-bar linkages using evolutionary algorithms (EAs). Usually, the design problem is assigned to minimize the error between desired and obtained coupler curves ...

Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation.

Human brain mapping
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinson's disease. While accurate localization of the STN is critical for consistent across-patients effective D...

Sparse Generative Topographic Mapping for Both Data Visualization and Clustering.

Journal of chemical information and modeling
To achieve simultaneous data visualization and clustering, the method of sparse generative topographic mapping (SGTM) is developed by modifying the conventional GTM algorithm. While the weight of each grid point is constant in the original GTM, it be...