Understanding Health and Nutrition through Data Science
Details
We are very excited to announce the next, 7th MeetUp, that will be held on 04.04.2019, Thursday, from 18:00 to 19:30 at INNOFEIT (FEEIT, Annex building).
Dr. Tome Eftimov will give an interesting talk about Data Science in health and nutrition.
Tome Eftimov is a postdoctoral researcher at Stanford University in USA. Previously, he was a researcher at the Computer Systems Department, Jožef Stefan Institute, in Ljubljana, Slovenia.
In 2018, he received his PhD degree in Information and Communication Technologies at the Jožef Stefan International Postgraduate School, Ljubljana, Slovenia.
The event is supported by INNOFEIT, GrabIT, IEEE Information Theory and IEEE Computer Chapters, and the faculties FEIT and FINKI.
Snacks and drinks provided by GrabIT :)
Agenda:
- 17:45 - 18:15 - Gathering and networking (snacks and drinks)
- 18:15 - 19:00 - Presentation by Tome Eftimov: Understanding Health and Nutrition through Data Science
- 19:00 - 19:15 - Networking (snacks and drinks)
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More information about the talk.
In the last decades, a lot of work is done in predictive modelling in healthcare. All this work is supported by existence of a number of available biomedical vocabularies and standards, and datasets. As a result the medical data can be used to find a patient's representation by projecting the data into a continuous vector space analyzed by machine learning and deep learning to perform predictive studies in healthcare. The first part of the talk will be focused on state-of-the-art medical embedding methods.
Furthermore, the Lancer Planetary Health published that the 2019 will be the year of nutrition, where the focus will be on the links between food systems, human health, and the environment. Contrary to the large number of available resources for the biomedical domain, there is still no annotated corpus with food concepts, and there are few rule-based food named-entity recognition systems that can be used for food concepts extraction. The second part of the talk will be focused on natural language processing and machine learning methods available for food and nutrition science.
The talk will also address several gaps that are important to be addressed in the near future in order to make a bridge between human health and food systems.