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Decision support in the intensive care unit: from models to applications. - Belgium
KU Leuven (company)
Posted on : 24 June 2017
- Critical Care Medicine is a relatively young branch in modern medicine.
- The first ICU’s started in the 1950’s, but it wasn’t until the 1970’s and1980’s that ICU’s boomed worldwide and the discipline quickly became a high-tech branch of medicine combining clinical skills, powerful drugs, and sophisticated mechanical devices to support the function of vital organs.
- This allows patients to survive a variety of previously lethal insults such as multiple trauma,extensive surgery or severe infections.
- Intensive care is sometimes referred to as “the art of managing extreme complexity”.
- Despite this dedicated care, mortality among critically ill patients who require intensive care for more than a few days remains around 20% worldwide.
- Critical illness affects millions of patients each year worldwide and consumes a large fraction of health care resources.
- It is therefore of great interest to detect as early as possible those patients most vulnerable to specific organ deterioration in order to administer dedicated therapies earlier and hopefully prevent the chronic and lethal phases of critical illness.
- The typical ICU generates vast amounts of data from several monitoring systems for each patient.
- At the department of intensive care medicine of the university hospitals , this data is electronically collected as time series of varying resolutions and integrated in a patient data management system (PDMS).
- Using data mining and machine learning techniques we have previously developed clinically relevant prediction models from the PDMS data, that outperform commonly used risk scores and that perform on par with experienced physicians.
- We have mainly focused on neuro-intensive care, and acute kidney injury.
- Our department has national and international collaborations to share data with other large ICU’s.
- We strongly believe the time is right to transition early detection models into intelligent warning systems to be used for decision support by the physician, on the daily evaluation of the individual ICU patients.
- Knowledge generation from ‘big data’is an important research path in modern medical science and our research group is at the forefront of this trend.
- Our interdisciplinary research team, where clinicians, basic biomedical scientists,computer scientists and engineers work in close collaboration is a unique environment. With the help of this interdisciplinary research team, the PhD candidate will gradually be able to acquire the knowledge and skills to perform in-depth analysis of PDMS data collected at our ICU to develop novel models for early detection of organ-specific critical illness.
- The ultimate goal of this project is to translate these models into bedside tools to be used in our ICU setting in a prospective randomized clinical trial.
Key words: clinical prediction models, decision support systems, machine learning, datamining, intensive care medicine
- The candidate should have a strong academic record and a Masters diploma in the fields of Bio-informatics, Computer Science or Engineering.
- Knowledge of data analysis, statistics, machine learning and good programming skills are essential. Knowledge of R, Matlab, Python and/or Weka is an advantage.
- Proficiency in written and spoken English is crucial.
- Previous research experience is a plus, but not essential.
- The candidate should be motivated to work with clinicians, in the design, development, and evaluation of decision support tools.
- This will require regular visits to the intensive care unit, at the bedside, as an observer without being directly involved in patient care.
- The selected candidate is expected to write a doctoral thesis on her/his research after 4 years.
- FulltimePhD position in an international research team.
- Our university is one of Europe's leading research universities, and tops Reuters ranking of Europe's most innovative universities.
- The Intensive Care Medicine Research Group offers a dynamic and intellectually challenging environment, in close collaboration with experts from a wide variety of domains.
- A thorough scientific education, the possibility to become a world-class researcher.
- The possibility to participate in international conferences and collaborations.