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An overview of Cerner Real World Data utility in human clinical research
Presenter:Mikhail Kovalenko
Date:11-30-2023
Time:4:00PM-4:30PM
Location:2501 MU Student Center
The widespread adoption of electronic health record (EHR) systems promises easier access and wealth of potentially useful data for patients and researchers. Oracle provides their compilation of de-identified patient records for research purposes that includes 1.8 billion encounters from more than 100 healthcare systems in the US as the Oracle/Cerner Real-World Data (CRWD) dataset. We
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Using Machine Learning for Predicting Survivability of Cancer Patients with Metastatic Patterns
Presenter:Polycarp Nalela
Date:11-30-2023
Time:3:30PM-4:00PM
Location:2501 MU Student Center
Cancer is one of the leading causes of death in the United States. In this study, we investigate how machine learning (ML) can be used to predict the survivability of cancer patients with metastatic patterns. We use the MSK-MET dataset, which is an integrated pan-cancer cohort of tumour genomic and clinical outcome data from 25,775
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Comprehensive Exam Announcement: A Comprehensive Suite of Tools for Allele Discovery and Phenotype Improvement in Crops
Presenter:Yen On Chan
Date:11-29-2023
Time:9:30AM-10:30AM
Location:Zoom
The rapid advancement in sequencing technologies has significantly enhanced sequencing efforts and created vast amounts of genomics and phenomics data over the years. The whole genome re-sequencing data has become an invaluable resource for scientific research to enable the precise identification of alleles and functional elements within genomes. By adopting data mining methodologies and integrating
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