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eBriefing

Improving Clinical Medicine with Computational Approaches

Improving Clinical Medicine with Computational Approaches
Reported by
Benjamin Ragen

Posted June 26, 2020

Presented By

The New York Academy of Sciences

The huge advances in computer technology and computational methods has transformed all fields of science, including medicine. In this eBriefing, experts discuss how Big Data, AI, and novel computational approaches have enabled doctors and scientists to make huge improvements in our ability to diagnose and treat a variety of diseases.

In this eBriefing, You’ll Learn:  

  • How the use of Big Data and Artificial Intelligence informs diagnosis and treatment for various medical conditions;
  • How the application of genomics in cancers can aid in targeted treatment approaches;
  • How mathematical modeling of cancer evolution can optimize anti-cancer treatments, as evidenced by pre-clinical trials designed to improve radiation for glioblastomas;
  • The next steps to using computational advances to improve healthcare.

Speakers

Olivier Elemento, PhD
Olivier Elemento, PhD

Weill Cornell Medicine

Franziska Michor, PhD
Franziska Michor, PhD

Dana-Farber Cancer Institute

Computational Approaches to Clinical Medicine

Speakers

Filtering is not allowed.

Computational Approaches to Clinical Medicine


Olivier Elemento/Franziska Michor (Weill Cornell Medicine/Dana-Farber Cancer Institute)
Olivier Elemento, PhD
Weill Cornell Medicine

Olivier Elemento, PhD, combines Big Data analytics with experimentation to develop entirely new ways to help prevent, diagnose, understand, treat and ultimately cure cancer. He is a Walter B. Wriston Research Scholar and Professor of Physiology and Biophysics at Weill Cornell Medicine. He is also the Director of the Englander Institute for Precision Medicine and Associate Director of the Institute for Computational Biomedicine. Elemento received his BS from Paul Sabatier University and his doctorate from CNRS/University of Montpellier. He was a postdoctoral research associate at Princeton University and joined Weill Cornell Medicine in 2008.

Franziska Michor, PhD
Dana-Farber Cancer Institute

Franziska Michor, PhD, utilizes theoretical evolutionary biology, applied mathematics, statistics, and computational biology to improve tumor diagnostics and anti-cancer treatment options in order to alleviate cancer-related morbidity and mortality. Dr. Michor is a Professor of Computational Biology in the Department of Data Sciences at the Dana-Farber Cancer Institute and the Department of Stem Cell and Regenerative Biology at Harvard University. She is also the Director of the Dana-Farber Cancer Institute Physical Sciences-Oncology Center and the Center for Cancer Evolution. Dr. Michor received her BS from the University of Vienna, Austria, and her PhD at Harvard University. She was a Junior Fellow in the Harvard Society of Fellows and joined the Dana-Farber Cancer Institute in 2010.

Further Readings

Michor

Altrock PM, Liu LL, Michor F

Nat Rev Cancer. 2015 Dec;15(12):730-745

Badri H, Pitter K, Holland EC, et al

J Math Biol. 2016 Apr;72(5):1301-1336