AIMC Topic: Support Vector Machine

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Machine learning-based modeling to predict inhibitors of acetylcholinesterase.

Molecular diversity
Acetylcholinesterase enzyme is responsible for the degradation of acetylcholine and is an important drug target for the treatment of Alzheimer's disease. When this enzyme is inhibited, more acetylcholine is available in the synaptic cleft for the use...

Diagnosis of Alzheimer's Disease by Time-Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal.

Computational and mathematical methods in medicine
Using strategies that obtain biomarkers where early symptoms coincide, the early detection of Alzheimer's disease and its complications is essential. Electroencephalogram is a technology that allows thousands of neurons with equal spatial orientation...

Research on nondestructive identification of grape varieties based on EEMD-DWT and hyperspectral image.

Journal of food science
Grape varieties are directly related to the quality and sales price of table grapes and consumed products (raisin, wine, grape juice, etc.). To satisfy the identification requirements of rapid, accurate, and nondestructive detection, an improved deno...

Simple action for depression detection: using kinect-recorded human kinematic skeletal data.

BMC psychiatry
BACKGROUND: Depression, a common worldwide mental disorder, which brings huge challenges to family and social burden around the world is different from fluctuant emotion and psychological pressure in their daily life. Although body signs have been sh...

Assessing Children's Fine Motor Skills With Sensor-Augmented Toys: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Approximately 5%-10% of elementary school children show delayed development of fine motor skills. To address these problems, detection is required. Current assessment tools are time-consuming, require a trained supervisor, and are not mot...

Magnetic properties and its application in the prediction of potentially toxic elements in aquatic products by machine learning.

The Science of the total environment
Magnetic measurement was provided to substitute for time-consuming conventional methods for determination of potentially toxic elements. Both the concentrations of 12 elements and 9 magnetic parameters were determined in 700 muscle tissue samples fro...

Distinguishing Rectal Cancer from Colon Cancer Based on the Support Vector Machine Method and RNA-sequencing Data.

Current medical science
Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Several studies have indicated that rectal cancer is significantly different from colon cancer in terms of treatment, prognosis, and metastasis. Recently, the differential...

iRNA-m5U: A sequence based predictor for identifying 5-methyluridine modification sites in Saccharomyces cerevisiae.

Methods (San Diego, Calif.)
The 5-methyluridine (mU)modification plays important roles in a series of biological processes. Accurate identification of mU sites will be helpful to decode its biological functions. Although experimental techniques have been proposed to detect mU, ...

An Explainable Artificial Intelligence Framework for the Deterioration Risk Prediction of Hepatitis Patients.

Journal of medical systems
In recent years, artificial intelligence-based computer aided diagnosis (CAD) system for the hepatitis has made great progress. Especially, the complex models such as deep learning achieve better performance than the simple ones due to the nonlinear ...