1E - Big Data, Machine Learning and Medicine
CME (AMA PRA Category 1 Credits™) 1.5; CEU (NSGC Category 1) 0.15; Attendance CEU 1.5

Monday, October 9
10:15 AM - 11:45 AM

Learning Objectives:

Konstantinos Lazaridis

Professor of Medicine, College of Medicine
Center for Individualized Medicine, Mayo Clinic

Konstantinos Lazaridis, MD, is a Professor of Medicine and a Consultant in the Division of Gastroenterology and Hepatology at Mayo Clinic College of Medicine. 

Dr. Lazaridis received his medical degree at the University of Ioannina in Greece. He completed his Internal Medicine and Gastroenterology fellowship training at Mayo Clinic and was a Mayo Clinic Scholar in Genomics in the laboratory of Dr. Francis Collins at the National Human Genome Research Institute. 
Dr. Lazaridis is considered a leader in the area of the genomics of chronic cholestatic liver diseases, namely, Primary Biliary Cirrhosis (PBC) and Primary Sclerosing Cholangitis (PSC). Since 2003, he has established and is the principal investigator of the two national consortia for studying patients afflicted with these diseases. His research group applies the latest genomic and genetic epidemiology approaches to better understand the pathogenesis and improve the therapy of patients with PBC and PSC. This research effort is supported by the NIH.

As Associate Director of the Center for Individualized Medicine in Rochester, Dr. Lazaridis has been instrumental in the establishment and expansion of the Individualized Medicine Clinic and the direction of the Clinomics translational program.

Presentation(s):

Send Email for Konstantinos Lazaridis

Eric W. Klee

Senior Associate Consultant II
Center for Individualized Medicine; Department of Health Sciences Research; Department of Clinical Genomics, Mayo Clinic

Eric W. Klee, PhD, is an Assistant Professor of Medical Informatics and Bioinformatics Program faculty member in the Department of Health Sciences Research, and has been at the Mayo Clinic since 2005. Dr. Klee is Director of Bioinformatics of Mayo Clinic’s Clinical Genome Sequencing Laboratory and member of the Department of Laboratory Medicine and Pathology, a position held since 2012. Dr. Klee is also the Associate Director of Mayo Clinic’s Center for Individualized Medicine Bioinformatics Program and has directed the Individualized Medicine Bioinformatics team since 2012.

Dr. Klee earned his Bachelors of Science degree in Electrical Engineering at Iowa State University in 1997, obtained a Master of Science degree in Health Informatics with focus in Bioinformatics at the University of Minnesota, Minneapolis. He went on to complete his PhD in Health Informatics and Bioinformatics in the University of Minnesota, Minneapolis, in 2005.

Dr. Klee’s research is focused on the application of next generation sequencing for clinical testing and diagnostics. His work includes the translation of emerging bioinformatics methods from the research domain into clinical practice. He is actively involved in the in development and implementation of systems to support sequence analysis and interpretation in the context of individualized, precision medicine. Dr. Klee also leads a functional validation program that uses experimental techniques to better characterize the putative role of variants of uncertain significance in the context of patient-specific disease state.

Presentation(s):

Send Email for Eric Klee

Ravishankar Iyer

Professor
Univ. of Illinois at Urbana-Champaign

Ravishankar K. Iyer, PhD, is George and Ann Fisher Distinguished Professor of Engineering at the University of Illinois at Urbana-Champaign. He holds joint appointments in the Departments of Electrical and Computer Engineering and Computer Science, in the Coordinated Science Laboratory (CSL) the National Center for Supercomputing Applications, and the Carl R. Woese Institute for Genomic Biology. He is also a faculty Research Affiliate at the Mayo Clinic. Professor Iyer leads the Depend Group at CSL which is focused on systems and software; deep measurement driven analytics combined with machine learning methods and data driven innovations with applications in two important domains: i) trust (that spans resilience and the security of critical infrastructures) and ii) health (that spans computational genomics and health analytics focused on personalized medicine. Working closely with Mayo Clinic, Professor Iyer's DEPEND Group has developed a rich data-driven analytics framework that is enabling discoveries in both clinical and biological settings. He currently co-leads the Computational Genomics - CompGen Initiative at Illinois and is the Principal Investigator for the Center for Computational Biology and Genomic Medicine CCGBM (an Industry/University Collaborative Research Center funded by the National Science Foundation). The CCBGM develops and promotes collaboration between academia, industry, hospitals, and research laboratories to utilize the power of computational predictive genomics to advance pressing health care and related computational biotechnology issues of significant industrial interest. Also funded by an NSF MRI grant is a new computational platform to address both accuracy and performance issues for a range of genomics applications. The DEPEND group also has extensive expertise in data analytics in the system resilience and security domains - a domain where his group has won several awards and recognitions in both in advanced data analytics and resilient system design in critical infrastructures.


Presentation(s):

Send Email for Ravishankar Iyer

Saurabh Sinha

Professor of Computer Science
University of Illinois at Urbana-Champaign

Saurabh Sinha is an Associate Professor of Computer Science at the University of Illinois, Urbana-Champaign. Sinha's research interests include computational regulatory genomics, cis-regulatory evolution, pharmacogenomics, and big-data for genomics. He is the Education Lead for the Mayo-Illinois Alliance, and serves as Research PI on the NIH BD2K Center at Illinois.

Presentation(s):

Send Email for Saurabh Sinha


Assets

1E - Big Data, Machine Learning and Medicine
CME (AMA PRA Category 1 Credits™) 1.5; CEU (NSGC Category 1) 0.15; Attendance CEU 1.5



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Send Email for Big Data, Machine Learning and Medicine
CME (AMA PRA Category 1 Credits™) 1.5; CEU (NSGC Category 1) 0.15; Attendance CEU 1.5