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Data Preprocessing And Machine Learning For Intracranial Electroencephalography, Mauricio Cespedes Tenorio
Data Preprocessing And Machine Learning For Intracranial Electroencephalography, Mauricio Cespedes Tenorio
Electronic Thesis and Dissertation Repository
This thesis serves to address the problem of non-standardized preprocessing of intracranial electroencephalography (iEEG) recordings by implementing a software workflow that compiles some of the most common steps followed for the preparation of this type of data. This workflow improves the consistency, replicability, and ease of use of iEEG preprocessing, facilitating the replication and extension of previous studies and the combination of separately preprocessed inter-institutional datasets. Automatic detection of artifacts for iEEG data was also explored as a potential step to include in the preprocessing workflow. Despite training the models with cross-institutional data, poor performance was observed when tested on …
Breast Cancer Risk In Women With Breast Bilateral Asymmetry: Machine Learning Based Risk Analysis And Mitigation Through Developing A Framework For Customized Bra Design, Xi Feng
Electronic Thesis and Dissertation Repository
Breast cancer is the most prevalent form of cancer globally, accounting for 12.5% of all new cases annually. Research has found a significant correlation between breast bilateral asymmetry and an increased risk of cancer, with women diagnosed with breast cancer having higher levels of bilateral asymmetrical breast volume. Unfortunately, 87% of women with breast asymmetry lack adequate tools for assessing their cancer risk. Early screening using bilateral asymmetry to predict a woman's long-term risk of breast cancer can help physicians make informed decisions about whether to recommend sequential imaging and the frequency of screening. Another important factor in understanding the …
Machine Learning Classifiers For Chronic Obstructive Pulmonary Disease Assessment Using Lung Ct Data., Halimah Alsurayhi
Machine Learning Classifiers For Chronic Obstructive Pulmonary Disease Assessment Using Lung Ct Data., Halimah Alsurayhi
Electronic Thesis and Dissertation Repository
Chronic Obstructive Pulmonary Disease (COPD) is a condition characterized by persistent inflammation and airflow blockages in the lungs, contributing to a significant number of deaths globally each year. To guide tailored treatment strategies and mitigate future risks, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) employs a multifaceted assessment system of COPD severity, considering patient's lung function, symptoms, and exacerbation history. COPD staging systems, such as the high-resolution eight-stage COPD system and the GOLD 2023 three staging systems, have been later developed based on these factors. Lung Computed Tomography (CT) is becoming increasingly crucial in investigating COPD as it …