Are you a data scientist or developer working in healthcare? Are you tired of dealing with proprietary data formats for biological and vital sign information? It's time to unlock the power of open data and make your research more impactful.

In this talk, we'll explore how you can leverage Python analytics to manipulate and analyze complex datasets of patient information, including blood work, ECG, EEG, echocardiography, radiography, and more.

We'll also dive into the world of open data formats, and show you how using these formats can make it easier to anonymize, convert, and collaborate on research.

Don't miss this opportunity to learn how Python analytics and open data formats can help you unlock the insights hidden in your data and improve patient outcomes.

In this talk, we'll explore the power of open data formats for healthcare and how Python analytics, like NumPy, SciPy, Pandas and Matplotlib, can be used to analyze and unlock the insights hidden in biomedical datasets. We'll dive into the world of open data formats, including EDF for ECG and EEG, ISHNE for Holter, FASTA, FASTQ and SAM for biological sequence data, DICOM for radiology, and more.

We'll also discuss the importance of adhering to open data format standards and avoiding proprietary extensions, which can limit collaboration and hinder progress in healthcare research. To help ensure compliance with these standards, we'll introduce a variety of Python libraries, like Biopython, MNE-Python, pydicom, EDFlib-Python and ISHNEHolterLib, that can be used to test output files and ensure they meet the required standard.

Whether you're a data scientist, developer, or healthcare professional, this talk is for you. By leveraging the power of open data formats and Python analytics, we can improve patient outcomes and advance the field of healthcare research. Join us as we explore the exciting possibilities of open data formats and Python analytics in healthcare.