At our third Lecture Series last week, Prof. Till Bärnighausen gave an interesting talk on „Integrating causal inference – from correlation to causation in ‘big data’ in health care and policy“.
The past 30 years have seen a revolution in causal inference in epidemiology and health policy research. New approaches to measurement of health-related data, such as sensors and cell phone data, as well as data linkage across many sources are massively increasing opportunities for causal evaluation of health policies and real-life interventions. The well-attended lecture by Prof. Bärnighausen described emerging methodological and data opportunities to establish causal impacts of health policies and interventions.
Last Saturday Prof. Katus welcomed the principal investigators at the annual meeting to present their progresses in the respective sub-projects. Also members of the Klaus Tschira Foundation joined the meeting to inform themselves about the development process.
Many Sub-projects have already networked and found approaches for joint projects and further developments, which will now be further specified and processed in the coming year.
At our second Lecture Series last week, Prof. Robert Preißner from the Charité in Berlin gave an interesting talk on the repositioning of drugs based on real-world evidence.
For the investigation, nearly half a million discharge letters from the Charité were evaluated and the findings were validated with results from colleagues in the USA. Prof. Preißner presented the results of this research. Also this event was attended very well.
“Artificial intelligence and digital twins in Healthcare – From advanced medical imaging to precision medicine” was the subject of our first lecture serie on June 27.
Artificial intelligence and digital twin technologies are poised to transform care delivery as we know it.
In Ph D. Tommaso Mansi’s lecture examples of applications were presented, going from improving workflows, to next generation medical image quantification and interpretation to the estimation of individualized computational models of a patient’s organ, called digital twins.
In particular, it was presented how a digital twin of a patient’s heart could be used to help disease characterization as well as plan and guide procedures, with the goal of improving outcomes.
We enjoyed the scientific excange and are looking forward to the next lectures.
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