Under Helmholtz Munich’s leadership, scientists have developed an easy-to-use software solution specifically for analyzing complex medical health data. Open source software called “ehrapy” allows researchers to build and systematically examine large heterogeneous datasets. The software is available for use and further development by the global scientific community.
Lukas Heumos, a scientist at the Helmholtz Institute for Computational Biology in Munich and Technical University of Munich (TUM), one of the lead developers, said Ehrapy aims to fill a key gap in health data analysis. “To date, there is no standardized tool to systematically and efficiently analyze diverse and complex medical data. We changed that with ehrapy,”Heumos said.
The team behind Eapy comes from biomedical research and has extensive experience in analyzing complex scientific datasets. “The health care sector faces challenges similar to those of laboratory work when it comes to data analysis,” Heumos pointed out at the beginning of the ehrapy project.
The study was published in the journal Nature Medicine.
Exploratory Method-Hypothesis Analysis
Heumos, along with many other contributors, used his expertise in scientific software development to create solutions for analyzing patient data. “Ehrapy can discover new patterns and generate insights without the need to analyze data based on specific assumptions or assumptions,” Heumos said. Heumos said this exploratory approach is unique to ehrapy.
Ehrapy allows researchers to sort, group, and analyze large, heterogeneous, and complex data sets without any pre-existing assumptions. This opens up new insights that can be explored further.
Heumos explained: “The exploratory approach brings new perspectives to health data analysis. Due to the complexity and heterogeneity of these data, these data often cannot be effectively analyzed.” As a result, Ehrrapy opens up new ways to make health data more useful for medical research and practice.
Long-term goal: Routine use in clinical practice
Ehrrapy has been designed as open source software from the beginning. “From day one, making this software available to the scientific community is very important for us,” Heumos emphasized.
The software is available as a Python package on GitHub, an online software development platform, and is available for use and further development by researchers around the world.
Currently, ehrapy focuses on efficiently and quickly analyzing research datasets, such as those stored in large health research centers. “Routine use in clinical practice is a long-term goal, but for now, we are focused on providing the research community with powerful tools,” Heumos said.
In the future, the team plans to provide a standardized database for electronic health records (EHR). These databases will be able to better integrate and analyze large amounts of medical data. In addition, this will facilitate the development of the EHR atlas, which can be used as a reference dataset for background and annotation of new datasets.
long journey
Professor Fabian Theis, director of the Helmholtz Institute for Computational Biology, said: “Ehrapy enables comprehensive data analysis across systems, which may be a critical step in future medical artificial intelligence systems. So I hope to be able to adopt it relatively quickly across sites.” Professor at Munich and Technical University of Munich. “Establishing such technologies in medicine is a long process and may take decades. Our goal is to bridge the gap between biomedical research and practical medical applications.”
Tais further explained that the development team is focusing on a holistic form of exploratory data analysis methods to more easily reveal hidden connections, adding: “We are also trying to support academic and business players in the health care space.”
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Original text:https://medicalxpress.com/news/2024-09-ehrapy-source-tool-complex-health.html
More information: Using ehrapy for exploratory electronic health record analysis, Nature Medicine (2024). DOI：10.1038/s41591-024-03214-0
Ehrapy on GitHub: https://github.com/theislab/ehrapy
Ehrrapy on GitHub: https://github.com/theislab/ehrapy
Journal information: Natural Medicine
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