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Full-Text Articles in Biomedical Engineering and Bioengineering

Subomiembed: Self-Supervised Representation Learning Of Multi-Omics Data For Cancer Type Classification, Sayed Hashim, Muhammad Ali, Karthik Nandakumar, Mohammad Yaqub Feb 2022

Subomiembed: Self-Supervised Representation Learning Of Multi-Omics Data For Cancer Type Classification, Sayed Hashim, Muhammad Ali, Karthik Nandakumar, Mohammad Yaqub

Computer Vision Faculty Publications

For personalized medicines, very crucial intrinsic information is present in high dimensional omics data which is difficult to capture due to the large number of molecular features and small number of available samples. Different types of omics data show various aspects of samples. Integration and analysis of multi-omics data give us a broad view of tumours, which can improve clinical decision making. Omics data, mainly DNA methylation and gene expression profiles are usually high dimensional data with a lot of molecular features. In recent years, variational autoencoders (VAE) [13] have been extensively used in embedding image and text data into …


Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub Jan 2022

Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub

Computer Vision Faculty Publications

Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are used to detect and segment the tumor region. Clinically, tumor segmentation is extensively time-consuming and prone to error. Machine learning, and deep learning in particular, can assist to automate this process, yielding results as accurate as the results of a clinician. In this research study, we develop a vision transformers-based method to automatically delineate H&N tumor, and compare its results to leading convolutional neural network (CNN)-based models. We use multi-modal data …


Blood Transfusions In Preterm Infants: Changes On Perfusion Index And Intermittent Hypoxemia, Katrina T. Ibonia, Henrietta S. Bada, Philip M. Westgate, Enrique Gomez Pomar, Prasad Bhandary, Abhijit R. Patwardhan, Elie G. Abu Jawdeh Nov 2018

Blood Transfusions In Preterm Infants: Changes On Perfusion Index And Intermittent Hypoxemia, Katrina T. Ibonia, Henrietta S. Bada, Philip M. Westgate, Enrique Gomez Pomar, Prasad Bhandary, Abhijit R. Patwardhan, Elie G. Abu Jawdeh

Pediatrics Faculty Publications

BACKGROUND

Red blood cell (RBC) transfusion decreases intermittent hypoxemia (IH) events beyond the first week of life. This benefit may be related to improved perfusion to the respiratory control network. Perfusion index (PI) is a perfusion measure provided by the pulse oximeter. We hypothesized that the benefit in IH after RBC transfusion is associated with an increase in PI. In addition, we assessed the value of PI and clinical measures in predicting the effect of RBC transfusion on IH.

STUDY DESIGN AND METHODS

We prospectively enrolled infants less than 30 weeks' gestation age. PI and oxygen saturation (SpO2) …


Bcc Skin Cancer Diagnosis Based On Texture Analysis Techniques, Shao-Hui Chuang, Xiaoyan Sun, Wen-Yu Chang, Gwo-Shing Chen, Adam Huang, Jiang Li, Frederic D. Mckenzie Jan 2011

Bcc Skin Cancer Diagnosis Based On Texture Analysis Techniques, Shao-Hui Chuang, Xiaoyan Sun, Wen-Yu Chang, Gwo-Shing Chen, Adam Huang, Jiang Li, Frederic D. Mckenzie

Electrical & Computer Engineering Faculty Publications

In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% …


Destruction Of Α -Synuclein Based Amyloid Fibrils By A Low Temperature Plasma Jet, Erdinc Karakas, Agatha Munyanyi, Lesley Greene, Mounir Laroussi Jan 2010

Destruction Of Α -Synuclein Based Amyloid Fibrils By A Low Temperature Plasma Jet, Erdinc Karakas, Agatha Munyanyi, Lesley Greene, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

Amyloid fibrils are ordered beta-sheet aggregates that are associated with a number of neurodegenerative diseases such as Alzheimer and Parkinson. At present, there is no cure for these progressive and debilitating diseases. Here we report initial studies that indicate that low temperature atmospheric pressure plasma can break amyloid fibrils into smaller units in vitro. The plasma was generated by the plasma pencil, a device capable of emitting a long, low temperature plasma plume/jet. This avenue of research may facilitate the development of a plasma-based medical treatment.