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Full-Text Articles in Biomedical Engineering and Bioengineering
2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh
2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh
SDSU Data Science Symposium
Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …
Understanding The Effect Of Adaptive Mutations On The Three-Dimensional Structure Of Rna, Justin Cook
Understanding The Effect Of Adaptive Mutations On The Three-Dimensional Structure Of Rna, Justin Cook
Undergraduate Research and Scholarship Symposium
Single-nucleotide polymorphisms (SNPs) are variations in the genome where one base pair can differ between individuals.1 SNPs occur throughout the genome and can correlate to a disease-state if they occur in a functional region of DNA.1According to the central dogma of molecular biology, any variation in the DNA sequence will have a direct effect on the RNA sequence and will potentially alter the identity or conformation of a protein product. A single RNA molecule, due to intramolecular base pairing, can acquire a plethora of 3-D conformations that are described by its structural ensemble. One SNP, rs12477830, which …
A Note From The Editor, Daphne Fauber
A Note From The Editor, Daphne Fauber
Ideas: Exhibit Catalog for the Honors College Visiting Scholars Series
This piece is a letter from Daphne Fauber, the editor of this issue of Ideas. In the letter, the editor introduces the work of Dr. Paschalis Gkoupidenis as well as the moment in time in which his Visiting Scholars talk occurs.
Transcriptomics To Develop Biochemical Network Models In Cyanobacteria, Bridget E. Hegarty, Jordan Peccia, Ratanachat Racharaks
Transcriptomics To Develop Biochemical Network Models In Cyanobacteria, Bridget E. Hegarty, Jordan Peccia, Ratanachat Racharaks
Yale Day of Data
Through targeted genetic manipulations guided by network modeling, we will create a flexible, cyanobacteria-based platform for the production of biofuel-precursors and valuable chemical products. To build gene-metabolite predictive models, we have characterized Synecococcus elongatus sp. UTEX 2973’s (henceforth, UTEX 2973) gene expression and metabolite production under a number of environmental conditions.
Asd Biomarker Detection On Fmri Images: Feature Learning With Data Corruptions By Analyzing Deep Neural Network Classifier Outcomes, Xiaoxiao Li 6984086
Asd Biomarker Detection On Fmri Images: Feature Learning With Data Corruptions By Analyzing Deep Neural Network Classifier Outcomes, Xiaoxiao Li 6984086
Yale Day of Data
Autism spectrum disorder (ASD) is a complex neurological and developmental disorder. It emerges early in life and is generally associated with lifelong disability. Finding the biomarkers associated with ASD is extremely helpful to understand the underlying roots of the disorder and find more targeted treatment. Previous studies suggested brain activations are abnormal in ASDs, hence functional magnetic resonance imaging (fMRI) has been used to identify ASD. In this work we addressed the problem of interpreting reliable biomarkers in classifying ASD vs. control; therefore, we proposed a 2-step pipeline: 1) classifying ASD and control fMRI images by deep neural network, and …