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Personal And Public Health Decisions In A New Open Data Reality

Identifying COVID-19 Instagram Behaviour Patterns via a Novel Network Analysis Pipeline

**BRACIS** originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – **SBIA** (22 editions), and the Brazilian Symposium on Neural Networks – **SBRN** (13 editions). **ENIAC** is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. **STIL** is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: **CE-IA**, **CE-IC** and **CE-PLN**.

To access the 10th Brazilian Conference on Intelligent Systems (**BRACIS**), you need to register for the conference.  Please visit the Conference official site to register

[Register now](http://c4ai.inova.usp.br/bracis2021/)

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BRACIS 2021

BRACIS originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – SBIA (22 editions), and the Brazilian Symposium on Neural Networks – SBRN (13 editions). 
ENIAC is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. 
STIL is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: CE-IA, CE-IC and CE-PLN

technical paper

The 2020 Undergraduate Big Data Challenge (BDC) and Big Data Day was revolutionized by the STEM Fellowship team to be held completely online in spite of COVID-19. This year’s theme of Personal and Public Health Decisions in a New Open Data Reality saw a diverse set of participants. There was a record-breaking number of registrations this year, with 523 participants in total, with 249 participants identifying as female, and 274 as male. The participants were joined by 48 mentors that guided and taught them. The challenge encouraged students to apply analytical and computational approaches to analyze the open data. 

The Big Data Day’s Roundtable discussed  “Science Communication at the time of urgent Personal and Public Health Decisions,” with Dr. Sacha Noukhovitch, the founder and president of STEM Fellowship, as the moderator. The invited panelists included: Deepak Kaura (the Chief Medical Officer for 1QBit), Suzanna Kettley (Executive Director of Canadian Science Publishing), Eleanor Haine-Bennet (Program Officer for Natural Sciences for Canadian Commission for UNESCO), and Michael Duong (Head of Personalized Healthcare Hoffmann-La Roche Ltd).

This year’s winners produced exceptional projects that explored various nuances relating to COVID-19 and more. Various projects have examined COVID-19 data to further understand the demographics of COVID-19 cases, both nationally and internationally. Some participants investigated topics ranging from the effects of social media on mental health, to COVID-19 Vulnerability in the U.S. Counties. Topics ranged from socioeconomics in health care to the significance of developing new methods for making decisions in health policies. These projects exhibited the accelerating progress of interdisciplinary research in health. 

The Big Data Challenge program ultimately aims to equip students with the power of Data Science to combat the most pressing issues our world faces. The winners and finalists of the BDC are already pursuing publication and venues to implement their findings. The youth are the foundation of new changes to come and it is our passion to actively foster them synergistically with their formal education. We will continue growing this initiative and program in the years to come with even greater impact.

National Inter-University Big Data Challenge 2020 -

Please find the top student research projects applying analytical and computational approaches to open and accessible data in order to probe and analyze personal and professional decision-making related to health.

Leveraging Machine Learning Methods toPredict COVID-19 Vulnerability in U.S. CountiesBased on Socioeconomic Factors

An Analysis of the COVID-19 Infodemic: The Extensive and Disproportionate Impact ofPublic FIgures on Public Behaviour and Sentiment Towards Hydroxychloroquine

Identifying COVID-19 Instagram Behaviour Patterns via a Novel Network Analysis Pipeline

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Identifying COVID-19 Instagram Behaviour Patterns via a Novel Network Analysis Pipeline

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Next from Personal And Public Health Decisions In A New Open Data Reality

Leveraging Machine Learning Methods toPredict COVID-19 Vulnerability in U.S. CountiesBased on Socioeconomic Factors

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Detecting Early Signs of Insufficiency in COVID-19 Patients from CBC Tests Through a Supervised Learning Approach

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES

Downloads