AIMC Topic: Machine Learning

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Symbiosis-Based Alternative Learning Multi-Swarm Particle Swarm Optimization.

IEEE/ACM transactions on computational biology and bioinformatics
Inspired by the ideas from the mutual cooperation of symbiosis in natural ecosystem, this paper proposes a new variant of PSO, named Symbiosis-based Alternative Learning Multi-swarm Particle Swarm Optimization (SALMPSO). A learning probability to sel...

Detection of concealed cars in complex cargo X-ray imagery using Deep Learning.

Journal of X-ray science and technology
BACKGROUND: Non-intrusive inspection systems based on X-ray radiography techniques are routinely used at transport hubs to ensure the conformity of cargo content with the supplied shipping manifest. As trade volumes increase and regulations become mo...

Multiple sensors-based kernel machine learning in smart environment.

The Review of scientific instruments
Sensor-based monitoring systems use multiple sensors to identify high-level information based on the events that take place in a monitored environment. Identification and health care are important tasks in the smart environment. This paper presents a...

Machine Learning and Molecular Dynamics Based Insights into Mode of Actions of Insulin Degrading Enzyme Modulators.

Combinatorial chemistry & high throughput screening
BACKGROUND: Alzheimer's disease (AD) is one of the most common lethal neurodegenerative disorders having impact on the lives of millions of people worldwide. The disease lacks effective treatment options and the unavailability of the drugs to cure th...

Learning-based deformable image registration for infant MR images in the first year of life.

Medical physics
PURPOSE: Many brain development studies have been devoted to investigate dynamic structural and functional changes in the first year of life. To quantitatively measure brain development in such a dynamic period, accurate image registration for differ...

Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

Journal of the Optical Society of America. A, Optics, image science, and vision
Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing pr...

Machine vision methods for analyzing social interactions.

The Journal of experimental biology
Recent developments in machine vision methods for automatic, quantitative analysis of social behavior have immensely improved both the scale and level of resolution with which we can dissect interactions between members of the same species. In this p...

Development of a Web-Enabled SVR-Based Machine Learning Platform and its Application on Modeling Transgene Expression Activity of Aminoglycoside-Derived Polycations.

Combinatorial chemistry & high throughput screening
OBJECTIVE: Support Vector Regression (SVR) has become increasingly popular in cheminformatics modeling. As a result, SVR-based machine learning algorithms, including Fuzzy-SVR and Least Square-SVR (LS-SVR) have been developed and applied in various r...

Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.

Methods in molecular biology (Clifton, N.J.)
Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional p...

PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia remains a significant challenge for improving the outcomes and decreasing the cost of healthca...