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DTSTART;TZID=Europe/Berlin:20241112T180000
DTEND;TZID=Europe/Berlin:20241112T193000
DTSTAMP:20260417T084419
CREATED:20240911T134258Z
LAST-MODIFIED:20240919T110704Z
UID:85452-1731434400-1731439800@www.hs-coburg.de
SUMMARY:Digitalization and artificial intelligence in personalized medicine: Who decides on my therapy?
DESCRIPTION: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.\nThis is also raising questions in healthcare and medicine: Will AI decide on my medication?\nWill we still need doctors in the future?\nTo what extent are AI and machine learning already being used?\nThese questions arise from uncertainties and fears.\nThe 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. \nThe 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.\nWe 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. \nProgram\nProModell: Digital twins for the treatment of neurological diseases\nDr. 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.\nNeuromodulation technologies can be used to specifically stimulate nerves in the spinal cord and brain.\nThe technology promises great therapeutic benefits.\nHowever\, 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.\nInnovative approaches such as machine learning and digital twins help to better understand how the technology interacts with the nervous system.\nThis can accelerate development and improve clinical decision-making.\nThe 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. \nTransparency writ large: Explainable AI models for the detection of biomarkers for diseases\nProf. 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.\nHowever\, transparency regarding the basis for decision-making is very important for successful use in medicine and targeted support in the medical environment.\nHow can the flood of medical data be analyzed by AI in an explainable way in order to classify diseases and identify biomarkers?\nTo 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.\nThis basic concept will be explained during the health theme evening using the example of cancer. \nHow does a medicine affect me?\nMachine learning in personalized medicine \nDr. Matthias Zwick\, Clinical Bioinformatics – Boehringer Ingelheim In cohort studies\, researchers collect data from a large group of study participants over several years.\nThis results in large data sets with many different types of measured values\, including genetic information.\nResearchers use machine learning methods to find characteristic features for diseases\, for example\, in these large amounts of data\, known as biomarkers.\nThese biomarkers can later be used for early detection\, diagnosis and therapy.\nMachine learning is used here to predict the effectiveness of a drug based on such biomarkers or certain patient characteristics.\nThis themed evening will explain this using specific application examples. \nHealth at the pulse of research\n      You are currently viewing a placeholder content from YouTube. To access the actual content\, click the button below. Please note that doing so will share data with third-party providers.  More Information   Unblock content Accept required service and unblock content   Registration\nPlease note: Your details will be sent to our server in encrypted form.\nYou agree that we may use the information to organize the event.\nYou can find our privacy policy here.    Please enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Name *VornameNachnameE-Mail *HinweisHiermit willige ich ein\, dass ich per E-Mail Hinweise zu ähnlichen Veranstaltungen erhalte.Datenschutz *Ich habe die Datenschutzerklärung der Hochschule Coburg gelesen und stimme der Verarbeitung meiner Daten für die Veranstaltung zu.Submit
URL:https://www.hs-coburg.de/en/veranstaltung/digitalization-and-artificial-intelligence-in-personalized-medicine-who-decides-on-my-therapy/
LOCATION:Alte Kühlhalle\, Schlachthofstr. 1\, Coburg\, 96450
CATEGORIES:External event
ORGANIZER;CN="Dr. Julia Kenzel":MAILTO:Julia.Kenzel@hs-coburg.de
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