AIMC Topic: Support Vector Machine

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Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques.

Scientific reports
The study aimed to achieve the following objectives: (1) to perform the fusion of thermal and visible tongue images with various fusion rules of discrete wavelet transform (DWT) to classify diabetes and normal subjects; (2) to obtain the statistical ...

Spontaneous brain activity in patients with central retinal artery occlusion: a resting-state functional MRI study using machine learning.

Neuroreport
Central retinal artery occlusion (CRAO) is a serious eye condition that poses a risk to vision, resulting from the blockage of the central retinal artery. Because of the anatomical connection between the ocular artery, which derives from the internal...

Rapid and nondestructive watermelon (Citrullus lanatus) seed viability detection based on visible near-infrared hyperspectral imaging technology and machine learning algorithms.

Journal of food science
The improper storage of seeds can potentially compromise agricultural productivity, leading to reduced crop yields. Therefore, assessing seed viability before sowing is of paramount importance. Although numerous techniques exist for evaluating seed c...

Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning.

Molecules (Basel, Switzerland)
The rapid and sensitive detection of pathogenic and suspicious bioaerosols are essential for public health protection. The impact of pollen on the identification of bacterial species by Raman and Fourier-Transform Infrared (FTIR) spectra cannot be ov...

Impact of economic indicators on rice production: A machine learning approach in Sri Lanka.

PloS one
Rice is a crucial crop in Sri Lanka, influencing both its agricultural and economic landscapes. This study delves into the complex interplay between economic indicators and rice production, aiming to uncover correlations and build prediction models u...

Predicting stroke events with a proactive fusion system: a comprehensive study on imbalance class handling in computational biomechanics.

Computer methods in biomechanics and biomedical engineering
Stroke, as a critical global health concern and the second leading cause of death, occurs when blood flow to the brain is interrupted. Although machine learning has advanced in medical safety, there is limited research on stroke prediction using info...

Machine learning-assisted matrix-assisted laser desorption/ionization time-of-flight mass spectrometry toward rapid classification of milk products.

Journal of dairy science
This study established a method for rapid classification of milk products by combining MALDI-TOF MS analysis with machine learning techniques. The analysis of 2 different types of milk products was used as an example. To select key variables as poten...

Potential of hyperspectral imaging for nondestructive determination of α-farnesene and conjugated trienol content in 'Yali' pear.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The sesquiterpene α-farnesene and its corresponding oxidation products, namely conjugated trienols (CTols) is well known to be correlated with the development of superficial scald, a typical physiological disorder after a long term of cold storage in...

Predicting PM2.5 concentration with enhanced state-trend awareness and uncertainty analysis using bagging and LSTM neural networks.

Journal of environmental quality
Monitoring air pollutants, particularly PM2.5, which refers to fine particulate matter with a diameter of 2.5 µm or smaller, has become a focal point of environmental protection efforts worldwide. This study introduces the concept of state-trend awar...

NNBGWO-BRCA marker: Neural Network and binary grey wolf optimization based Breast cancer biomarker discovery framework using multi-omics dataset.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Breast cancer is a multifaceted condition characterized by diverse features and a substantial mortality rate, underscoring the imperative for timely detection and intervention. The utilization of multi-omics data has gained ...