AIMC Topic: Machine Learning

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Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals.

Computational intelligence and neuroscience
Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlie...

Early Detection of Ureteropelvic Junction Obstruction Using Signal Analysis and Machine Learning: A Dynamic Solution to a Dynamic Problem.

The Journal of urology
PURPOSE: We sought to define features that describe the dynamic information in diuresis renograms for the early detection of clinically significant hydronephrosis caused by ureteropelvic junction obstruction.

Machine learning applied to neuroimaging for diagnosis of adult classic Chiari malformation: role of the basion as a key morphometric indicator.

Journal of neurosurgery
OBJECTIVE The current diagnostic criterion for Chiari malformation Type I (CM-I), based on tonsillar herniation (TH), includes a diversity of patients with amygdalar descent that may be caused by a variety of factors. In contrast, patients presenting...

Learning-based deformable registration for infant MRI by integrating random forest with auto-context model.

Medical physics
PURPOSE: Accurately analyzing the rapid structural evolution of human brain in the first year of life is a key step in early brain development studies, which requires accurate deformable image registration. However, due to (a) dynamic appearance and ...

A New Approach to Predict user Mobility Using Semantic Analysis and Machine Learning.

Journal of medical systems
Mobility prediction is a technique in which the future location of a user is identified in a given network. Mobility prediction provides solutions to many day-to-day life problems. It helps in seamless handovers in wireless networks to provide better...

A machine learning method for fast and accurate characterization of depth-of-interaction gamma cameras.

Physics in medicine and biology
Measuring the depth-of-interaction (DOI) of gamma photons enables increasing the resolution of emission imaging systems. Several design variants of DOI-sensitive detectors have been recently introduced to improve the performance of scanners for posit...

A new machine-learning method to prognosticate paraquat poisoned patients by combining coagulation, liver, and kidney indices.

PloS one
The prognosis of paraquat (PQ) poisoning is highly correlated to plasma PQ concentration, which has been identified as the most important index in PQ poisoning. This study investigated the predictive value of coagulation, liver, and kidney indices in...

Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning.

JACC. Cardiovascular imaging
OBJECTIVES: This study evaluated the added predictive value of combining clinical information and myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) data using machine learning (ML) to predict major adverse cardiac ...

Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology.

Neural networks : the official journal of the International Neural Network Society
A novel, unsupervised nonparametric model of multivariate probability density functions (pdf) is introduced, namely the Parzen neural network (PNN). The PNN is intended to overcome the major limitations of traditional (either statistical or neural) p...