Physical Sciences and Mathematics Commons^™

Deep Learning Applications In Medical Bioinformatics, Ziad Omar

Electronic Theses and Dissertations

After a patient’s breast cancer diagnosis, identifying breast cancer lymph node metastases is one of the most important and critical factor that is directly related to the patient’s survival. The traditional way to examine the existence of cancer cells in the breast lymph nodes is through a lymph node procedure, biopsy. The procedure process is time-consuming for the patient and the provider, costly, and lacks accuracy as not every lymph node is examined. The intent of this study is to develop an artificial neural network (ANNs) that would map genetic biomarkers to breast lymph node classes using ANNs. The neural …

Impact Of Neoantigen Expression And T-Cell Activation On Breast Cancer Survival, Wenjing Li, Amei Amei, Francis Bui, Saba Norouzifar, Lingeng Lu, Zuoheng Wang

Mathematical Sciences Faculty Research

Neoantigens are derived from tumor-specific somatic mutations. Neoantigen-based syn-thesized peptides have been under clinical investigation to boost cancer immunotherapy efficacy. The promising results prompt us to further elucidate the effect of neoantigen expression on patient survival in breast cancer. We applied Kaplan–Meier survival and multivariable Cox regression models to evaluate the effect of neoantigen expression and its interaction with T-cell activation on overall survival in a cohort of 729 breast cancer patients. Pearson’s chi-squared tests were used to assess the relationships between neoantigen expression and clinical pathological variables. Spearman correlation analysis was conducted to identify correlations between neoantigen expression, mutation …

Defying The Darkness: Countering Cancer With Light, Travis Hankins

Honors Theses

Triple-Negative Breast Cancer (TNBC) accounts for upwards of 15% of reported breast cancer cases. This subtype of breast cancer poses a greater threat to those diagnosed as compared to other types of breast cancer due to the lack of treatment options available. Additionally, TNBC grows and spreads faster, tends to be more aggressive, and has a greater chance of recurrence than its counterparts. Altogether, TNBC cases generally have a worse prognosis over other types of breast cancer. Photodynamic therapy (PDT) is currently being researched as a way to treat TNBC. Photodynamic therapy agents are light-activated materials used for localized disease …

Co-Phosphorylation Networks Reveal Subtype-Specific Signaling Modules In Breast Cancer, Marzieh Ayati, Mark R. Chance, Mehmet Koyuturk

Computer Science Faculty Publications and Presentations

Motivation Protein phosphorylation is a ubiquitous mechanism of post-ranslational modification that plays a central role in cellular signaling. Phosphorylation is particularly important in the context of cancer, as down-regulation of tumor suppressors and up-regulation of oncogenes by the dysregulation of associated kinase and phosphatase networks are shown to have key roles in tumor growth and progression. Despite recent advances that enable large-scale monitoring of protein phosphorylation, these data are not fully incorporated into such computational tasks as phenotyping and subtyping of cancers.

Results We develop a network-based algorithm, CoPPNet, to enable unsupervised subtyping of cancers using phosphorylation data. For this …

A Novel Hybrid K-Means And Gmm Machine Learning Model For Breast Cancer Detection, P. Esther Jebarani, N. Umadevi, Helen Dang, Marc Pomplun

Faculty Works: MCS (1984-2023)

Breast cancer is the second leading cause of death among a large number of women worldwide. It may be challenging for radiologists to diagnose and treat breast cancer. Consequently, primary care improves disease prevention and death. Early detection increases treatment options and saves life, which is the major target of this research. This research indicates the versatility of the methodology by integrating contemporary segmentation approaches with machine learning methods, which are developing areas of research. In the pre-processing process, an adaptive median filter is utilized for noise removal, enhancement of image quality, conservation of edges, and smoothing. This research makes …

Bypassing The Blood-Brain Barrier: A Physical And Pharmacological Approach For The Treatment Of Metastatic Brain Tumors, Samuel A. Sprowls

Graduate Theses, Dissertations, and Problem Reports

This dissertation (a) provided an in depth literature review of methods to disrupt the BBB/BTB and improve therapeutic distribution to brain tumors, (b) evaluated the use of azacitidine as a single agent therapy for the treatment of brain metastasis of breast cancer and a potential molecular mechanism by which brain tropic cells are sensitized to hypomethylating agents, (c) determined the impact cannabidiol has on P-glycoprotein mediated efflux at the blood-brain barrier and its potential for use as a single agent treatment for metastatic brain tumors, (d) developed a preclinical radiation therapy protocol for use in small animals and in vitro …

Branched-Chain Amino Acids And Risk Of Breast Cancer, Oana A. Zeleznik, Raji Balasubramanian, Yumeng Ren, Deirdre K. Tobias, Bernard A. Rosner, Cheng Peng, Alaina M. Bever, Lisa Frueh, Sarah Jeanfavre, Julian Avila-Pacheco, Clary B. Clish, Samia Mora, Frank B. Hu, A. Heather Eliassen

Biostatistics and Epidemiology Faculty Publications Series

Background

Circulating branched-chain amino acid (BCAA) levels reflect metabolic health and dietary intake. However, associations with breast cancer are unclear. Methods

We evaluated circulating BCAA levels and breast cancer risk within the Nurses’ Health Study (NHS) and NHSII (1997 cases and 1997 controls). A total of 592 NHS women donated 2 blood samples 10 years apart. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) of breast cancer risk in multivariable logistic regression models. We conducted an external validation in 1765 cases in the Women’s Health Study (WHS). All statistical tests were 2-sided. Results

Among NHSII participants (predominantly premenopausal …

Automated Classification Of Bi-Rads In Textual Mammography Reports, Mostafa Boroumandzadeh, Elham Parvinnia

Turkish Journal of Electrical Engineering and Computer Sciences

The main purpose of this paper is to process key information in medical text records and also classifypatients, per different levels of breast imaging-reporting and data system (BI-RADS). The BI-RADS is a scheme for thestandardization of breast imaging reports. Therefore, medical text mining is employed to classify mammography reportssupported BI-RADS. In this research, a new method is proposed for automated BI-RADS classifications extraction fromtextual reports and improves the therapeutic procedures. At first, a mammography lexicon is employed for choosingkeywords from medical text reports. Word2vec and term frequency inverse document frequency (TFIDF) techniques areused for extracting features, finally, they are combined …

Green Biosynthesis, Characterization, And Cytotoxic Effect Of Magnetic Iron Nanoparticles Using Brassica Oleracea Var Capitata Sub Var Rubra (Red Cabbage) Aqueous Peel Extract, Ömer Erdoğan, Sali̇h Paşa, Gülen Meli̇ke Demi̇rbolat, Özge Çevi̇k

Turkish Journal of Chemistry

The green method of nanoparticle synthesis, which is an environment and living-friendly method, is an updated subject that has appeared as an alternative to conventional methods such as physical and chemical synthesis. In this presented study, the green synthesis of magnetic iron oxide nanoparticles (IONPs) from iron (III) chloride by using Brassica oleracea var. capitata sub.var. rubra aqueous peel extract has been reported. The prepared IONPs were characterized with fourier-transform infrared spectroscopy (FT-IR), ultraviolet-visible spectroscopy (UV-VIS), zeta potential, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDX). The cytotoxic effects of IONPs on MCF-7 breast cancer cell line were studied …

Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel ultrawide band (UWB) antipodal Vivaldi antenna with three pairs of slots was designed to be used as a sensor in microwave imaging systems for breast cancer detection. The proposed antenna operates in UWB frequency range of 3.05-12.2 GHz. FR4 was used as a dielectric material and as a substrate for forming the antenna that has a compact size of 36 mm x 36 mm x 1.6 mm. Frequency and time domain performance of the proposed antenna have been investigated and results show that it meets the requirements for UWB radar applications with linear phase response, …

Improved Cell Segmentation Using Deep Learning In Label-Free Optical Microscopyimages, Aydin Ayanzadeh, Özden Yalçin Özuysal, Devri̇m Pesen Okvur, Sevgi̇ Önal, Behçet Uğur Töreyi̇n, Devri̇m Ünay

Turkish Journal of Electrical Engineering and Computer Sciences

The recently popular deep neural networks (DNNs) have a significant effect on the improvement of segmentation accuracy from various perspectives, including robustness and completeness in comparison to conventional methods. We determined that the naive U-Net has some lacks in specific perspectives and there is high potential for further enhancements on the model. Therefore, we employed some modifications in different folds of the U-Net to overcome this problem. Based on the probable opportunity for improvement, we develop a novel architecture by using an alternative feature extractor in the encoder of U-Net and replacing the plain blocks with residual blocks in the …