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71 results about "Phenome" patented technology

A phenome is the set of all phenotypes expressed by a cell, tissue, organ, organism, or species. Just as the genome and proteome signify all of an organism's genes and proteins, the phenome represents the sum of its phenotypic traits. Examples of human phenotypic traits are skin color, eye color, body height, or specific personality characteristics. Although any phenotype of any organism has a basis in its genotype, phenotypic expression may be influenced by environmental influences, mutation, and genetic variation such as single nucleotide polymorphisms (SNPs), or a combination of these factors.

Improved deep Boltzmann machine-based pulmonary nodule feature extraction and benign and malignant classification method

ActiveCN107316294APreserve the original nodule informationGuaranteed accuracyImage enhancementImage analysisPulmonary noduleLearning machine
The present invention discloses an improved deep Boltzmann machine-based pulmonary nodule feature extraction and benign and malignant classification method. The method includes the following steps that: step A, pulmonary nodules are segmented from CT images through using a threshold probability image graph method, so that regions of interest (ROI) are obtained, and the regions of interest are cut into nodule images of the same size; and step B, a supervised deep learning algorithm Pnd-EBM is designed to realize the diagnosis of a pulmonary nodule, wherein the diagnosis of the pulmonary nodule further includes three major steps: B1, a deep Boltzmann machine (DBM) is adopted to extract the features of the ROI of the pulmonary nodule which have deep expression abilities; B2, a sparse cross-entropy penalty factor is adopted to improve a cost function, so that the phenomenon of feature homogenization in a training process can be avoided; and B3, an extreme learning machine (ELM) is adopted to perform benign and malignant classification on the extracted features of the pulmonary nodule. The improved deep Boltzmann machine-based pulmonary nodule feature extraction method is superior to a traditional feature extraction method. With the method adopted, the complexity of manual extraction and the difference of feature selection can be avoided, and references can be provided for clinical diagnosis.
Owner:TAIYUAN UNIV OF TECH

DCNN (Deep Convolutional Neural Network)-DNN (Deep Neural Network) and PV-SVM (Paragraph Vector-Support Vector Machine)-based multi-modal depressive disorder estimation and classification method

The invention relates to a DCNN (Deep Convolutional Neural Network)-DNN (Deep Neural Network) and PV-SVM (Paragraph Vector-Support Vector Machine)-based multi-modal depressive disorder estimation and classification method. The method comprises the following steps: preprocessing audio and video features through a displacement range histogram and an Opensmile tool, extracting hidden layer abstract features of audio and video statistical features through a DCNN, performing depressive disorder estimation through a DNN, performing high-dimensional feature mapping on textile information through a PV method, inputting an obtained high-dimensional feature expression into an SVM for binary classification, connecting a depressive disorder estimation result with a binary classification result in series, inputting the whole into a random forests model for training, and performing a final depressive disorder classification task through the trained random forests model, namely judging a depressive disorder or a non depressive disorder. By the adoption of a DCNN model for extraction of the hidden layer abstract features from a primary audio/video, an original high-dimensional feature is more compact, and included information is richer; therefore, the model is more effective, and the phenomenon of overfitting caused by extremely high dimension of the feature is avoided.
Owner:NORTHWESTERN POLYTECHNICAL UNIV

Molecular marker closely linked with oil content character of rapes and application

The invention discloses a molecular marker closely linked with an oil content character of the rapes and an application of the molecular marker. The molecular marker BrSF34-123 closely linked with the oil content character of the rapes comprises the following screening steps: 1) hybridizing a cabbage type rape variety zy036 and 51070 so as to obtain a DH generation segregation population; 2) designing a primer to polymorphically screen a parent, and establishing a genetic linkage map; 3) carrying out an field experiment and harvesting for the DH generation segregation population to obtain a phenome database of the oil content; and 4) carrying out QTL (quantitative trait locus) detection by combining the genetic linkage map of the developed high-density molecular marker with a genotype of the segregation population and the phenome database of the oil content to obtain the molecular marker closely linked with the oil content character of rapes. Therefore, the marker is utilized to be conducted for marker-assisted selection, thereby being capable of quickly screening the strains with high oil content for breeding the oil content of the rapes, being definite in breeding selection target and saving cost.
Owner:武汉中油种业科技有限公司
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