Training: Second Level Community
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Item A Multivariate Biomarker for Parkinson’s Disease(In the Proceedings of 12th Annual Research Day, 2014 - Pace University, 2015-05-15) Crocetti, Giancarlo; Coakley, Michael; Dressner, Phil; Kellum, Wanda; Lamin, TambaIn this study, we executed a genomic analysis with the objective of selecting a set of genes (possibly small) that would help in the detection and classification of samples from patients affected by Parkinson Disease. We performed a complete data analysis and during the exploratory phase, we selected a list of differentially expressed genes. Despite their association with the diseased state, we could not use them as a biomarker tool. Therefore, our research was extended to include a multivariate analysis approach resulting in the identification and selection of a group of 20 genes that showed a clear potential in detecting and correctly classify Parkinson Disease samples even in the presence of other neurodegenerative disorders.Item Transforming telemedicine through big data analytics(In the Proceedings of 12th Annual Research Day, 2014 - Pace University, 2015-05-15) Coakley, Michael; Crocetti, Giancarlo; Dressner, Phil; Kellum, Wanda; Lamin, TambaA look at how big data is transforming telemedicine to provide better care by tapping into a larger source of patient information. Telemedicine will have a profound impact on patient care, increase access and quality, and represent an opportunity to keep health care costs down. Data generated by smart devices will enable the real-time monitoring of chronic diseases, allowing optimal dosage of drugs and improve patient outcomes