AIMC Topic: Machine Learning

Clear Filters Showing 20901 to 20910 of 34417 articles

A scoping review of machine learning in psychotherapy research.

Psychotherapy research : journal of the Society for Psychotherapy Research
Machine learning (ML) offers robust statistical and probabilistic techniques that can help to make sense of large amounts of data. This scoping review paper aims to broadly explore the nature of research activity using ML in the context of psychologi...

Pain phenotypes classified by machine learning using electroencephalography features.

NeuroImage
Pain is a multidimensional experience mediated by distributed neural networks in the brain. To study this phenomenon, EEGs were collected from 20 subjects with chronic lumbar radiculopathy, 20 age and gender matched healthy subjects, and 17 subjects ...

A review of Cloud computing technologies for comprehensive microRNA analyses.

Computational biology and chemistry
Cloud computing revolutionized many fields that require ample computational power. Cloud platforms may also provide huge support for microRNA analysis mainly through disclosing scalable resources of different types. In Clouds, these resources are ava...

Computational Method for Quantitative Comparison of Activity Landscapes on the Basis of Image Data.

Molecules (Basel, Switzerland)
Activity landscape (AL) models are used for visualizing and interpreting structure-activity relationships (SARs) in compound datasets. Therefore, ALs are designed to present chemical similarity and compound potency information in context. Different t...

Forty years of emergency medicine research: Uncovering research themes and trends through topic modeling.

The American journal of emergency medicine
STUDY OBJECTIVE: Topic identification can facilitate knowledge curation, discover thematic relationships, trends, and predict future direction. We aimed to determine through an unsupervised, machine learning approach to topic modeling the most common...

Random Forests Approach for Causal Inference with Clustered Observational Data.

Multivariate behavioral research
There is a growing interest in using machine learning (ML) methods for causal inference due to their (nearly) automatic and flexible ability to model key quantities such as the propensity score or the outcome model. Unfortunately, most ML methods for...

Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning.

European journal of radiology
PURPOSE: During the emerging COVID-19 pandemic, radiology departments faced a substantial increase in chest CT admissions coupled with the novel demand for quantification of pulmonary opacities. This article describes how our clinic implemented an au...