AI Medical Compendium Topic

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Gas Recognition in E-Nose System: A Review.

IEEE transactions on biomedical circuits and systems
Gas recognition is essential in an electronic nose (E-nose) system, which is responsible for recognizing multivariate responses obtained by gas sensors in various applications. Over the past decades, classical gas recognition approaches such as princ...

Fourier transform infrared spectrum pre-processing technique selection for detecting PYLCV-infected chilli plants.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Pre-processing is a crucial step in analyzing spectra from Fourier transform infrared (FTIR) spectroscopy because it can reduce unwanted noise and enhance system performance. Here, we present the results of pre-processing technique optimization to fa...

Land Resource Use Classification Using Deep Learning in Ecological Remote Sensing Images.

Computational intelligence and neuroscience
Aiming at the problems that the traditional remote sensing image classification methods cannot effectively integrate a variety of deep learning features and poor classification performance, a land resource use classification method based on a convolu...

DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data.

PLoS computational biology
Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional ma...

Quantitative analysis of Raman spectra for glucose concentration in human blood using Gramian angular field and convolutional neural network.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this study, convolutional neural network based on Gramian angular field (GAF-CNN) was firstly proposed. The 1-D Raman spectral data was converted into images and used for predicting the biochemical value of blood glucose. 106 sets of blood spectru...

Differentially Private Singular Value Decomposition for Training Support Vector Machines.

Computational intelligence and neuroscience
Support vector machine (SVM) is an efficient classification method in machine learning. The traditional classification model of SVMs may pose a great threat to personal privacy, when sensitive information is included in the training datasets. Princip...

Fruit classification using attention-based MobileNetV2 for industrial applications.

PloS one
Recent deep learning methods for fruits classification resulted in promising performance. However, these methods are with heavy-weight architectures in nature, and hence require a higher storage and expensive training operations due to feeding a larg...

Mood State Detection in Handwritten Tasks Using PCA-mFCBF and Automated Machine Learning.

Sensors (Basel, Switzerland)
In this research, we analyse data obtained from sensors when a user handwrites or draws on a tablet to detect whether the user is in a specific mood state. First, we calculated the features based on the temporal, kinematic, statistical, spectral and ...

Near-Infrared Spectral Characteristic Extraction and Qualitative Analysis Method for Complex Multi-Component Mixtures Based on TRPCA-SVM.

Sensors (Basel, Switzerland)
Quality identification of multi-component mixtures is essential for production process control. Artificial sensory evaluation is a conventional quality evaluation method of multi-component mixture, which is easily affected by human subjective factors...

Machine Learning-Based Cry Diagnostic System for Identifying Septic Newborns.

Journal of voice : official journal of the Voice Foundation
BACKGROUND AND OBJECTIVE: Processing the newborns' cry audio signal (CAS) provides valuable information about the newborns' condition. This information can be used to diagnose the disease. This article analyzes the CASs of newborns under two months o...