AIMC Topic: Support Vector Machine

Clear Filters Showing 1251 to 1260 of 4975 articles

Raman spectroscopy combined with a support vector machine algorithm as a diagnostic technique for primary Sjögren's syndrome.

Scientific reports
The aim of this study was to explore the feasibility of Raman spectroscopy combined with computer algorithms in the diagnosis of primary Sjögren syndrome (pSS). In this study, Raman spectra of 60 serum samples were acquired from 30 patients with pSS ...

Diagnosis of liver diseases based on artificial intelligence.

Biotechnology & genetic engineering reviews
Due to a series of problems in the diagnosis of liver disease, the mortality rate of liver disease patients is very high. Therefore, it is necessary for doctors and researchers to find a more effective non-invasive diagnostic method to meet clinical ...

Rapid quantification of royal jelly quality by mid-infrared spectroscopy coupled with backpropagation neural network.

Food chemistry
Royal jelly is rich in nutrients but its quality is greatly affected by storage conditions. To determine the quality of royal jelly accurately and quickly, a qualitative discrimination model was established based on the fusion of conventional paramet...

Prediction of enzymatic function with high efficiency and a reduced number of features using genetic algorithm.

Computers in biology and medicine
The post-genomic era has raised a growing demand for efficient procedures to identify protein functions, which can be accomplished by applying machine learning to the characteristics set extracted from the protein. This approach is feature-based and ...

Application of a developed triple-classification machine learning model for carcinogenic prediction of hazardous organic chemicals to the US, EU, and WHO based on Chinese database.

Ecotoxicology and environmental safety
Cancer, the second largest human disease, has become a major public health problem. The prediction of chemicals' carcinogenicity before their synthesis is crucial. In this paper, seven machine learning algorithms (i.e., Random Forest (RF), Logistic R...

Support Vector Machine-Based Global Classification Model of the Toxicity of Organic Compounds to .

Molecules (Basel, Switzerland)
is widely used as the model species in toxicity and risk assessment. For the first time, a global classification model was proposed in this paper for a two-class problem (Class - 1 with log1/IBC ≤ 4.2 and Class + 1 with log1/IBC > 4.2, the unit of I...

Machine learning and deep learning based on the small FT-MIR dataset for fine-grained sampling site recognition of boletus tomentipes.

Food research international (Ottawa, Ont.)
This study proposed the necessity of identifying the sampling sites for Boletus tomentipes (B.tomentipes) in combination with cadmium content and environmental factors. Based on fourier transform mid-infrared spectroscopy (FT-MIR) preprocessing by 1s...

Machine Learning Hybrid Model for the Prediction of Chronic Kidney Disease.

Computational intelligence and neuroscience
To diagnose an illness in healthcare, doctors typically conduct physical exams and review the patient's medical history, followed by diagnostic tests and procedures to determine the underlying cause of symptoms. Chronic kidney disease (CKD) is curren...

Research on Supply Chain Financial Risk Prevention Based on Machine Learning.

Computational intelligence and neuroscience
Artificial intelligence (AI) proves decisive in today's rapidly developing society and is a motive force for the evolution of financial technology. As a subdivision of artificial intelligence research, machine learning (ML) algorithm is extensively u...

Efficient Selection of Gaussian Kernel SVM Parameters for Imbalanced Data.

Genes
For medical data mining, the development of a class prediction model has been widely used to deal with various kinds of data classification problems. Classification models especially for high-dimensional gene expression datasets have attracted many r...