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Full-Text Articles in Biomedical Informatics
Machine Learning Quantification Of High-Resolution Tissue Microarray (Tma) Image On Muc13 Ihc Analysis, Beibei Huang, Aiko Yamaguchi, Jianbo Wang, Shilpa Sharma, Zhiwen Liu, Henry Charles Manning
Machine Learning Quantification Of High-Resolution Tissue Microarray (Tma) Image On Muc13 Ihc Analysis, Beibei Huang, Aiko Yamaguchi, Jianbo Wang, Shilpa Sharma, Zhiwen Liu, Henry Charles Manning
Research Symposium
Background High-resolution tissue microarray (TMA) technology allows prompt molecular profiling of multiple tissue specimens, making it ideal for analyzing candidate biomarkers quickly and effectively [1, 2]. Integrating TMA with digital pathology and machine learning enhances high-throughput, cost-effective studies, offering advanced image analysis and improved diagnostic accuracy. MUC13 (Mucin 13) is a transmembrane glycoprotein frequently overexpressed in colorectal cancer (CRC) [3]. MUC13 contributes to colonic tumorigenesis, progression and metastasis [4, 5], making it an attractive target for antibody-guided radiotheranostics in CRC. This study investigates the expression pattern of MUC13 and its association with patients' clinical characteristics in primary and metastatic CRC …
Gene Co-Expression Networks And Descriptive Statistical Patterns In Cancer Subtypes, Arely Solis, Marzieh Ayati
Gene Co-Expression Networks And Descriptive Statistical Patterns In Cancer Subtypes, Arely Solis, Marzieh Ayati
Research Symposium
There are many cancers that are affecting the human population, with some being more common and studied than others. These cancers have mostly been studied individually until 2012 when scientists began studying through comparison analysis of different cancers to see possible connections on the genomic and molecular level and have resulted in the categorization of tumors into types. The result from molecular analysis has re-classified types of tumors into new clusters, which aid doctors in deciding the optimal way of treating tumors. In this study, we analyze a dataset comprising over 2,000 cancer samples, focusing on six cancer types: breast, …
Optimization Of Gait Analysis System For Clinical Applications, Gerardo Medellin, Katherine S. Bolado, Daniel Salinas, Kelsey Potter-Baker
Optimization Of Gait Analysis System For Clinical Applications, Gerardo Medellin, Katherine S. Bolado, Daniel Salinas, Kelsey Potter-Baker
Research Symposium
Background: Adequate gait function is pivotal for many activities of daily living and high quality of life. Following many neurodegenerative diseases, such as Parkinson’s Disease, gait abnormalities can manifest and range from reduced stride length, inability to turn, foot drop or shuffling. To track and monitor such changes in gait, gait analysis techniques are gaining clinical popularity and have the ability to gather a range of data in a short duration. Gait analysis techniques go beyond simple visual observation and include instrumental gait analysis and weight distribution of the gait cycle. Here, we sought to optimize the gait analysis …
Assessing Gait Metrics For Early Parkinson's Disease Prediction: A Preliminary Analysis Of Underfit Models, Daniel Salinas, Gerardo Medellin, Katherine Bolado, Tomas Gomez, Kelsey Potter-Baker, Nawaz Khan Abdul Hack, Ramu Vadukapuram
Assessing Gait Metrics For Early Parkinson's Disease Prediction: A Preliminary Analysis Of Underfit Models, Daniel Salinas, Gerardo Medellin, Katherine Bolado, Tomas Gomez, Kelsey Potter-Baker, Nawaz Khan Abdul Hack, Ramu Vadukapuram
Research Symposium
Background: Parkinson's Disease (PD) is characterized by both motor and non-motor symptoms, and its diagnosis primarily relies on clinical presentation. There is a growing need for diagnostic tools to identify the early signs of PD, particularly the initial motor impairments often manifested as gait abnormalities. Here we seek to present preliminary findings to address this need. Our study focuses on using Machine Learning techniques (ML) to predict the PD clinical stage most efficiently and accurately. Specifically, we have sought to evaluate how spatiotemporal characteristics and other locomotor performance variables obtained on a walkway system can be utilized to identify the …