AIMC Topic: Machine Learning

Clear Filters Showing 26031 to 26040 of 34417 articles

Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction.

Psychological science
Matchmaking companies and theoretical perspectives on close relationships suggest that initial attraction is, to some extent, a product of two people's self-reported traits and preferences. We used machine learning to test how well such measures pred...

Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting.

Medical physics
PURPOSE: The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid ar...

Elastic network model of learned maintained contacts to predict protein motion.

PloS one
We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein's contact topology. Existing elastic network models assume that the contact topology r...

LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks.

IEEE transactions on visualization and computer graphics
Recurrent neural networks, and in particular long short-term memory (LSTM) networks, are a remarkably effective tool for sequence modeling that learn a dense black-box hidden representation of their sequential input. Researchers interested in better ...

What Would a Graph Look Like in this Layout? A Machine Learning Approach to Large Graph Visualization.

IEEE transactions on visualization and computer graphics
Using different methods for laying out a graph can lead to very different visual appearances, with which the viewer perceives different information. Selecting a "good" layout method is thus important for visualizing a graph. The selection can be high...

Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning.

Perspectives on psychological science : a journal of the Association for Psychological Science
Psychology has historically been concerned, first and foremost, with explaining the causal mechanisms that give rise to behavior. Randomized, tightly controlled experiments are enshrined as the gold standard of psychological research, and there are e...

Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment.

Scientific reports
Rhegmatogenous retinal detachment (RRD) is a serious condition that can lead to blindness; however, it is highly treatable with timely and appropriate treatment. Thus, early diagnosis and treatment of RRD is crucial. In this study, we applied deep le...

Machine Learning Approaches on Diagnostic Term Encoding With the ICD for Clinical Documentation.

IEEE journal of biomedical and health informatics
This work focuses on data mining applied to the clinical documentation domain. Diagnostic terms (DTs) are used as keywords to retrieve valuable information from electronic health records. Indeed, they are encoded manually by experts following the Int...

A Machine Learning Approach to Automated Gait Analysis for the Noldus Catwalk System.

IEEE transactions on bio-medical engineering
OBJECTIVE: Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Nold...