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Digitalization and artificial intelligence in personalized medicine: Who decides on my therapy?

The development of artificial intelligence (AI) is currently increasing rapidly in all areas and is also playing an ever greater role in our everyday lives.
This is also raising questions in healthcare and medicine: Will AI decide on my medication?
Will we still need doctors in the future?
To what extent are AI and machine learning already being used?
These questions arise from uncertainties and fears.
The themed evening “Artificial intelligence in personalized medicine: Who decides on my therapy?” sheds light on the opportunities of AI and machine learning for personalized medicine and their possible applications.

The evening will provide an insight into what is currently being researched in Coburg and at Friedrich-Alexander-Universität Erlangen-Nürnberg in order to bring AI and machine learning into clinical application and also to what extent the pharmaceutical industry is already using such approaches in the field of personalized medicine.
We would then like to discuss with you what should be considered when using AI for medicine and how the use and application of AI can be presented transparently.

Program

Dr. Andreas Rowald, Group Leader for Digital Health at FAU Erlangen-Nuremberg The need for treatment options for diseases of the nervous system is increasing, not least due to demographic change.
Neuromodulation technologies can be used to specifically stimulate nerves in the spinal cord and brain.
The technology promises great therapeutic benefits.
However, its clinical application has so far been very complex and often relies on trial and error, as disease manifestations and patients differ individually and there has been a lack of decision-making aids to date.
Innovative approaches such as machine learning and digital twins help to better understand how the technology interacts with the nervous system.
This can accelerate development and improve clinical decision-making.
The ProModell research group develops digital twins to optimize neurostimulation strategies and presents impressive successes – for example, the restoration of walking ability after paraplegia in less than 24 hours.

Prof. Dr. Stefan Simm, Professor of Bioinformatics at Coburg University of Applied Sciences In the case of AI models that are designed as a “black box”, it is not possible to understand how a decision is made by the artificial intelligence.
However, transparency regarding the basis for decision-making is very important for successful use in medicine and targeted support in the medical environment.
How can the flood of medical data be analyzed by AI in an explainable way in order to classify diseases and identify biomarkers?
To this end, a working group at Coburg University of Applied Sciences is developing explainable AI models with the addition of biological information in order to train the AI transparently.
This basic concept will be explained during the health theme evening using the example of cancer.

Dr. Matthias Zwick, Clinical Bioinformatics – Boehringer Ingelheim In cohort studies, researchers collect data from a large group of study participants over several years.
This results in large data sets with many different types of measured values, including genetic information.
Researchers use machine learning methods to find characteristic features for diseases, for example, in these large amounts of data, known as biomarkers.
These biomarkers can later be used for early detection, diagnosis and therapy.
Machine learning is used here to predict the effectiveness of a drug based on such biomarkers or certain patient characteristics.
This themed evening will explain this using specific application examples.

Health at the pulse of research

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Hinweis
Datenschutz

12.11.2024 | 18:00 Uhr - 19:30 Uhr

Veranstaltungskategorie:

external event

Website:

Ansprechperson

Dr. Julia Kenzel

Telefon:

09561 317-8120

E-Mail:

Julia.Kenzel@hs-coburg.de

Veranstaltungsort

Alte Kühlhalle,Schlachthofstr. 2, Coburg

Schlachthofstr. 2

96450,

Coburg

https://maps.google.com/maps?f=q&source=s_q&hl=en&geocode=&q=Schlachthofstr.+2+Coburg+96450+Deutschland

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