Informatics for Life meets eCardiology

IFL Scientists presented interactive workshops

This year, our scientists were again actively involved as part of the eCardiology section at the annual meeting of the German Society for Cardiology in Mannheim. In addition to the many exciting lectures at the conference, they presented workshops and demonstrations on digital topics in medicine in the modern ambience of the Ella & Louis. Anyone who wanted could immerse oneself in the virtual world with AR glasses or test various mobile sensors and find out about their benefits. New useful apps, a demonstration of ChatGPT and even genetic sequencing could be tried out with the help of a cleverly constructed Lego model. Illustrative models familiarised visitors with 3D printing and lifelike simulations in cardiac surgery.

You can see a small selection of what was presented here in the video by Dr. Heart (from minute 8:00).


Symposium HEALTHY AI

AI meets Medicine: Promises and limits

In a relaxed atmosphere in the common room of the mathematical institute, this topic was discussed in various facets and from different perspectives.

Whether the topic was “Model-driven or Data-driven” or the question was “Games, Gadgets or AI: What will transform our lives?” – the discussions were stimulated by short keynote speeches and then actively discussed in the auditorium.

The keynote by Professor Steven Niederer (King’s College London) on the topic of “Computational Modeling: Prime time for the clinics” was also discussed controversially and was a real highlight.

Finally the speakers and the audience argued about what is already possible – Real-world implementation of data science and AI.

All day long the posters from this year’s competition were issued. The best placed won the Informatics for Life Award which was given for the third time.

Congratulate to this year’s winner, Malte Tölle.

New professorship “Precision Digital Health”

Our PI Benjamin Meder has accepted the call to the W3 professorship “Precision Digital Health” at Heidelberg University. As part of the research professorship, his focus is on molecular and digital biomarkers, the use of artificial intelligence in everyday clinical practice and wearables.


Informatics for Life Teams finished at the HeidelbergMan Triathlon 2022

In almost perfect weather (it could have been a bit cooler), the athletes faced the competition course, which is beautiful and demanding at the same time.

The swimmers jump into the cool water at the old bridge to the Neckarwiese and hand over to the cyclists there. His path runs twice on the Königsstuhl on a wooded circuit. The last stage takes the runner up the Philosophenweg and finally back down to the finish line on the Neckarwiese.

Congratulations to our Informatics for Life Teams, who finished with a top time and deservedly enjoyed this year’s finisher medals.

Special thanks go to the Klaus Tschira Foundation for the great support and of course to our fans.


I4L – Yearly Meeting

Our yearly meeting on November 13th was joined by an incredible number of participants. Also Ms Spiegel an Ms Spahn from the Klaus Tschira Stiftung signed in.

This years speakers illuminated not only their field of research but also the state of the art and other new innovations so that we got a colorful and varied overview.

We also started our “Informatics for Life Best Poster Award” which 13 young scientists took part in and presented their projects. In the end, the jury awarded two first prizes. They go to David Lehmann, as well as to Roger Karl and Lalith NagSharan Gururaj.



Deep Characterization of circular RNAs from human cardiovascular cell models and cardiac tissue

Our new study was undertaken to help to uncover potential functions of circular RNAs (circRNAs) that are relevant in cardiovascular disease (CVD) in cardiac model systems and organisms. The study defines a strongly conserved core set of circRNAs in human heart tissue, human induced pluripotent stem cell-derived cardiac myocytes (hiPSC-CMs), as well as mouse and pig heart. These circRNAs are promising potential targets for further studies because their function is likely conserved and therefore may be important in development and progression of CVD.

We employed a specialized deep sequencing approach to generate comprehensive maps of circRNA exon composition in hiPSC-CMs, human umbilical vein cells (HUVECs), and human hearts, which are required for more confident functional studies.

We identified shared circRNAs across all samples, as well as model-specific circRNA signatures and moreover identified a core set of positionally conserved and expressed circRNAs in human, pig, and mouse hearts. Furthermore, we found that the sequence of circRNAs can deviate from the sequence derived from the genome sequence, an important factor in assessing potential functions. Integration of additional data yielded evidence for m6A-modification of circRNAs, potentially linked to translation as well as circRNAs overlapping with potential Agonaut2 binding sites, indicating potential association with the RISC complex.

Moreover, we describe, for the first time in cardiac model systems, a sub class of circRNAs containing the start codon of their primary transcript (AUG circRNAs) and observe an enrichment for m6A-modifications and ribosome association.


Digitalization against social isolation – patients and doctors at Heidelberg University Hospital benefit from digital solutions

“Due to my previous illness, this is not my first stay in hospital, but the current situation makes it very difficult for me to keep my hopes up alive,” said Isolde Peters (name changed), 92-year-old heart patient who has been at Heidelberg University Hospital for seven days. Due to the nationwide COVID-19 protection measures, she is largely isolated from the social world outside. “I hardly see my children and my grandchildren live in the US. I worry every day.”

On initiative of the Heidelberg research network Informatics for Life the “#Hearts-against-Covid” campaign was launched bringing patients and their relatives virtually together. Thanks to a generous donation from the Klaus Tschira Foundation, tablet computers for video telephony were purchased enabling patients without smartphones to access virtual communication. “Before, I could not have imagined this, but when you are isolated in hospital, the greatest joy of my day is to see my grandchildren smile at me and to see that everyone is doing well,” says Isolde Peters visibly relieved.

“We have created a new way of communication for patients during these difficult times. Seeing their family is more than just entertainment. It is medicine,” said Benjamin Meder, member of the board of directors of Informatics for Life. “In the meantime we have not only created new possibilities for our patients, but we are also conducting all physician training courses via the digital channel.” Heidelberg medical students are also involved in the project helping patients to use the new technology and providing them with advice and support.

Professor Meder’s team also views the digital approaches as a long-term solution to various issues. For example, virtual meetings can help to conserve valuable resources and to reduce greenhouse gases in the future.

Foto: Medical student from Heidelberg is taking part in a virtual training course at the Department of Cardiology, Angiology and Pneumology (Director: Hugo A. Katus). The students are also very committed to explaining the new technology to patients.

Prognoses with the help of artificial intelligence

How long should a patient stay hospitalized after surgery, what conditions affect the recovery and how can we care for our patients in an optimal way?

With the help of Artificial Intelligence and a specially programmed algorithm, our assistant physician, Dr. Bruna Gomes, addresses the questions in her current research project on patients with heart valve diseases after a Transfemoral Catheter Assisted Aortic Valve Replacement (TAVI).

Computer programs with artificial intelligence (AI) are initially “fed” with numerous patient data sets and search this mass of digital data for predictive factors in order to predict certain events (e.g. complications or mortality).

While traditional statistical methods and classical risk scores take into account only about 10 characteristics of a patient in this probability calculation, the algorithm developed by Dr. Gomes – through Machine Learning – captures about 80 characteristics, learns continuously and gives a much more differentiated picture of the patient. “You can compare it to a photo that traditionally has 500 pixels, but our algorithm now allows us to display this image with 4000 pixels, giving us a much higher resolution image,” Dr. Bruna Gomes explains.

With this highly-differentiated image of the patient, Gomes and her colleagues in Prof. Benjamin Meder’s research team hope to improve the assessment of each individual patient in order to enable the best possible prediction of the course of our patients’ disease according to TAVI.

Currently, the algorithm is based on the already evaluated findings of a patient, but the goal is to evaluate imaging diagnostics (CT, MRI, Echocardiography) also by AI, to integrate them into the algorithm and to combine all available information.