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Wavelet Analysis

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Learning Spatial-Spectral-Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mental workload assessment is essential for maintaining human health and preventing accidents. Most research on this issue is limited to a single task. However, cross-task assessment is indispensable for extending a pre-trained model to new workload ...

MRI Brain Tumour Segmentation Using Hybrid Clustering and Classification by Back Propagation Algorithm.

Asian Pacific journal of cancer prevention : APJCP
Generally the segmentation refers, the partitioning of an image into smaller regions to identify or locate the region of abnormality. Even though image segmentation is the challenging task in medical applications, due to contrary image, local observa...

High quality imaging from sparsely sampled computed tomography data with deep learning and wavelet transform in various domains.

Medical physics
PURPOSE: Sparsely sampled computed tomography (CT) has been attracting attention as a technique that can reduce the high radiation dose of conventional CT. In general, iterative reconstruction techniques have been applied to sparsely sampled CT to re...

Artificial Intelligence Based Skin Classification Using GMM.

Journal of medical systems
This study describes the usage of neural community based on the texture evaluation of pores and skin a variety of similarities in their signs, inclusive of Measles (rubella), German measles (rubella), and Chickenpox etc. In fashionable, these illness...

Applying machine learning to continuously monitored physiological data.

Journal of clinical monitoring and computing
The use of machine learning (ML) in healthcare has enormous potential for improving disease detection, clinical decision support, and workflow efficiencies. In this commentary, we review published and potential applications for the use of ML for moni...

Wheeze type classification using non-dyadic wavelet transform based optimal energy ratio technique.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Wheezes in pulmonary sounds are anomalies which are often associated with obstructive type of lung diseases. The previous works on wheeze-type classification focused mainly on using fixed time-frequency/scale resolution base...

A Machine Learning Shock Decision Algorithm for Use During Piston-Driven Chest Compressions.

IEEE transactions on bio-medical engineering
GOAL: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The best current methods are computationally demanding, and their accuracy ...

Rainfall time series disaggregation in mountainous regions using hybrid wavelet-artificial intelligence methods.

Environmental research
In mountainous regions, rainfall can be extremely variable in space and time. The need to simulate rainfall time series at different scales on one hand and the lack of recording such parameters in small scales because of administrative and economic p...

A Survey on Machine Learning Approaches for Automatic Detection of Voice Disorders.

Journal of voice : official journal of the Voice Foundation
The human voice production system is an intricate biological device capable of modulating pitch and loudness. Inherent internal and/or external factors often damage the vocal folds and result in some change of voice. The consequences are reflected in...

Aiding the Digital Mammogram for Detecting the Breast Cancer Using Shearlet Transform and Neural Network.

Asian Pacific journal of cancer prevention : APJCP
Objective: Breast Cancer is the most invasive disease and fatal disease next to lung cancer in human. Early detection of breast cancer is accomplished by X-ray mammography. Mammography is the most effective and efficient technique used for detection ...