AIBE Researchers Uncover Pregnancy Symptom Insights Through Keleya App Data!

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Kurt Fuchs

Under the coordination of Prof. Dr. Björn Eskofier from the Machine Learning and Data Analytics Lab at AIBE, alongside Prof. Dr. Matthias W. Beckmann and Prof. Dr. Peter A. Fasching, the SMART Start Project has revealed crucial insights into pregnancy symptoms using data from the Keleya app. Analyzing over 183,000 users and 1.5 million symptoms, the study uncovered specific timelines for common discomforts like fatigue, backache, and trouble sleeping.

Michael Nissen, research associate and doctoral candidate at the Machine Learning and Data Analytics Lab, highlighted that fatigue peaks in the first trimester, headaches emerge around the 15th week, while issues like diarrhea fluctuate, reaching a minimum around week 20. These symptoms may have broader implications for birth risks and maternal mental health, emphasizing the need for further investigation.

Overall, this research covers lesser-known or debated symptoms and their progression, surpassing previous studies in scope. It underscores the potential of using sector data collaboratively between science and industry, paving the way for groundbreaking scientific discoveries.

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Prof. Björn can also be reached at for further inquiries.