Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jan 16, 2017
In this work, the data fusion strategy of Fourier transform mid infrared (FT-MIR) spectroscopy and inductively coupled plasma-atomic emission spectrometry (ICP-AES) was used in combination with Support Vector Machine (SVM) to determine the geographic...
In this paper, a novel classification technique for large data set of mammograms using a deep learning method is proposed. The proposed model targets a three-class classification study (normal, malignant, and benign cases). In our model we have prese...
Suberoylanilide hydroxamic acid (SAHA) exerts marked anticancer effects via promotion of apoptosis, cell cycle arrest, and prevention of oncogene expression. In this study, serum metabolomics and artificial intelligence recognition were used to inves...
As one of the most abundant RNA post-transcriptional modifications, N-methyladenosine (mA) involves in a broad spectrum of biological and physiological processes ranging from mRNA splicing and stability to cell differentiation and reprogramming. Howe...
IEEE/ACM transactions on computational biology and bioinformatics
Jan 10, 2017
Self interacting proteins (SIPs) play an important role in various aspects of the structural and functional organization of the cell. Detecting SIPs is one of the most important issues in current molecular biology. Although a large number of SIPs dat...
Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human-computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently ...
Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among...
. The purpose of this research is to develop a diagnostic method of diabetes based on standardized tongue image using support vector machine (SVM). Tongue images of 296 diabetic subjects and 531 nondiabetic subjects were collected by the TDA-1 digit...
Cell membrane permeability is an important determinant for oral absorption and bioavailability of a drug molecule. An in silico model predicting drug permeability is described, which is built based on a large permeability dataset of 7488 compound ent...
BACKGROUND: This study specifically focused on anatomical MRI characterization of the low shear stress-induced atherosclerotic plaque in mice. We used machine learning algorithms to analyze multiple correlation factors of plaque to generate predictiv...
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