Objective To establish a regression algorithm model that applies to bone age estimation of Xinjiang Uygur adolescents with machine learning methods such as histogram of oriented gradient （HOG）, local binary patterns （LBP）, support vector machine （SVM...
OBJECTIVES: To explore infrared spectrum characteristics of different voltages induced electrical injuries on swine skin by using Fourier transform infrared-microspectroscopy （FTIR-MSP） combined with machine learning algorithms, thus to provide a ref...
OBJECTIVES: To propose an alternative solid phase extraction-gas chromatography-mass spectrometry （SPE-GC-MS） method for the sensitive determination of cathinones in human urine samples, plus methodological verification.
OBJECTIVES: To develop a liquid chromatography-tandem mass spectrometry （LC-MS/MS） analytical method for the determination of oleandrin in blood and liver tissues, which could be applied to the cases of death caused by oleander poisoning.
OBJECTIVES: To realize the automated bone age assessment by applying deep learning to digital radiography （DR） image recognition of left wrist joint in Uyghur teenagers, and explore its practical application value in forensic medicine bone age assess...
Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech reco...
OBJECTIVES: To establish a gas chromatographic-mass spectrometric （GC-MS） analysis method for quantifying 1-methylhydantoin concentration in whole blood. To provide technical support to forensic identification related cases of 1-methylhydantoin.
OBJECTIVES: To study the content variation of selegiline and its metabolites in urine, and based on actual cases, to explore the feasibility for the identification of methamphetamine abuse and selegiline use by chiral analysis.