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SUMMARY:IC Colloquium : Clinical Text Understanding and Decision Support
DTSTART:20170302T101500
DTEND:20170302T113000
DTSTAMP:20260509T131724Z
UID:0c89912d774cdf569f8bee0b002f65b3bdceb72c9fd3395810dd8624
CATEGORIES:Conferences - Seminars
DESCRIPTION:By : Carsten Eickhoff - ETH Zurich\nIC Faculty candidate\n\nAb
 stract :\nClinical research has never been more active and diverse than it
  is at this moment. Research efforts span national and cultural borders an
 d broad online dissemination makes insights available at a global scale wi
 th ever decreasing latency. In the face of these developments\, individual
  researchers and practitioners are confronted with a seemingly intractable
  amount of material (approximately 1 Million scholarly articles are newly 
 published in the life sciences each year). While highly trained human expe
 rts excel at making precision diagnoses\, coverage\, especially for uncomm
 on conditions could be greatly improved. In this talk\, we will discuss a
  range of (deep) machine learning techniques that provide automatic clinic
 al decision support on the basis of large-scale data collections. Concrete
 ly\, I will present early and ongoing work on a) Patient-centric clinical 
 literature retrieval\, automatically identifying research papers\, clinica
 l trials and case reports that are relevant given the case at hand. b) Pre
 dictive assistants in post-operative care of cardiac surgery patients\, th
 at serve as early warning systems in case of undesirable and dangerous com
 plications. c) Data-driven diagnosis of rare diseases that individually oc
 cur too infrequently to allow clinical specialists to establish the necess
 ary routine and experience. \nTo close\, I will give a brief outlook on a
  wider range of future directions towards providing medical professionals 
 with powerful aggregates of their large-scale clinical information resourc
 es. In this way\, our work facilitates everyday medical practice as well a
 s clinical research beyond their current\, perceived limitations\, leading
  to the development of new treatments\, and\, ultimately\, improved patien
 t well-being. \n\nBio :\nCarsten is a researcher and lecturer at ETH Zuri
 ch\, specializing in clinical data science and information retrieval. He o
 btained his Ph.D. in computer science from the Technical University of Del
 ft in the Netherlands and an M.Sc. in artificial intelligence from the Uni
 versity of Edinburgh in Scotland. He has authored more than 50 conference 
 and journal articles on topics pertaining to automatic large-scale text pr
 ocessing and retrieval as well as information extraction from unstructured
  natural language resources.\n\nMore information
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
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