Parallel session on Improving healthcare through big data. Last findings of BigMedilytics (BigMedilytics project sponsored session)

November 5, 2020 - 14:00 - 15:00
Application Track 2 - Health
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The BigMedilytics (Big Data for Medical Analytics) project is one of the largest EU-funded “Lighthouse” initiatives to transform the region’s healthcare sector by using state-of-the-art big data technologies to achieve breakthrough productivity in the sector by reducing cost, improving patient outcomes and delivering better access to healthcare facilities simultaneously. The project implements 12 different pilots that span across 3 themes: Population Health (e.g. Cardiology, Diabetes, Comorbidities, etc.), Oncology (Prostate, Breast and Lung cancers) and Industrialization of Healthcare (which refers to the optimization of workflows within hospitals, e.g. Radiology or the management of Stroke and Sepsis patients).

The objective of the session is to share the current status of one pilot for each of the different themes covered by the BigMedilytics project (Kidney disease, Lung cancer, and Radiology workflows pilots) and gather the contributions of attendees through the interaction with the speakers generating a fruitful discussion around big data and artificial intelligence in healthcare.

From the Population Health theme, the last updates of the Kidney Disease pilot will be introduced. The goal of this pilot is to reduce hospitalizations and graft loss for kidney transplant patients. The pilot uses big data analytics and machine learning to help reveal patterns and risk factors that are relevant for long-term transplant survival.

In the case of the Oncology theme, the current status of lung-cancer pilot will be presented. This pilot aims to help oncologists to improve patient outcomes, while at the same time reducing costs. It currently aims to drill into sub-populations of patients, through filtering so as to facilitate personalised decisions. In particular we will demonstrate the factors that are related to the length of hospitalization, as well the services used before being diagnosed with lung-cancer. Moreover, the pilot provides direct access to lung-cancer knowledge graph, as well as a question-answer module focused on oncological drugs.

Finally, regarding the Industrialization of Healthcare, a demonstration will be run of the scientific methodology behind contextflow’s 3D image search and disease pattern detection for radiologists using artificial intelligence.
Alexandra Muñoz
Science communicator at INCLIVA
Dimitrios Vogiatzis
Research Associate & Co-ordinator of the MS in Data Science at ACG, Deree at NCSR "Demokritos" & The American College of Greece, Deree
Georg Langs
Chief Scientist and Co-Founder at contextflow
Wiebke Düttmann-Rehnolt
M.D. at Charité-Universitätsmedizin Berlin
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