HEALTHINF 2024 · Conference presentation

Synergizing data imputation and electronic health records for prostate cancer research

22 February 2024 Rome, Italy

Conference panel at BIOSTEC and HEALTHINF 2024 in Rome

Photo from my HEALTHINF 2024 conference post.

I presented our paper at HEALTHINF 2024, the 17th International Conference on Health Informatics, in Rome, Italy.

The work addresses a practical challenge in clinical research: electronic health records contain valuable information, but it is often split between incomplete structured fields and unstructured clinical notes. We developed and validated a pipeline that uses the overlap between these sources to extract prostate cancer data and build more complete, reliable research datasets.

The paper, Synergizing Data Imputation and Electronic Health Records for Advancing Prostate Cancer Research: Challenges, and Practical Applications, was published in the BIOSTEC 2024 — HEALTHINF proceedings, pages 77–86. The publication and open preprint are linked below.

Read the research behind this presentation.

2024

biostec
Synergizing Data Imputation and Electronic Health Records for Advancing Prostate Cancer Research: Challenges, and Practical Applications

Oussama Batouche, Eugen Czeizler, Miika Koskinen, Tuomas Mirtti, and Antti Sakari Rannikko

In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF, 2024

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Google Scholar 5 citations

The presence of detailed clinical information in electronic health record (EHR) systems presents promising prospects for enhancing patient care through automated retrieval techniques. Nevertheless, it is widely acknowledged that accessing data within EHRs is hindered by various methodological challenges. Specifically, the clinical notes stored in EHRs are composed in a narrative form, making them prone to ambiguous formulations and highly unstructured data presentations, while structured reports commonly suffer from missing and/or erroneous data entries. This inherent complexity poses significant challenges when attempting automated large-scale medical knowledge extraction tasks, necessitating the application of advanced tools, such as natural language processing (NLP), as well as data audit techniques. This work aims to address these obstacles by creating and validating a novel pipeline designed to extract relevant data pertaining to prostate cancer patients. The objective is to exploit the inherent redundancies available within the integrated structured and unstructured data entries within EHRs in order to generate comprehensive and reliable medical databases, ready to be used in advanced research studies. Additionally, the study explores potential opportunities arising from these data, offering valuable prospects for advancing research in prostate cancer.
@inproceedings{batouche_biostec, title = {Synergizing Data Imputation and Electronic Health Records for Advancing Prostate Cancer Research: Challenges, and Practical Applications}, author = {Batouche, Oussama and Czeizler, Eugen and Koskinen, Miika and Mirtti, Tuomas and Rannikko, Antti Sakari}, booktitle = {Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF}, year = {2024}, pages = {77-86}, publisher = {SciTePress}, organization = {INSTICC}, doi = {10.5220/0012350300003657}, isbn = {978-989-758-688-0}, issn = {2184-4305}, url = {https://www.scitepress.org/Link.aspx?doi=10.5220/0012350300003657}, dimensions = {true}, }

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