IA non stop

Friday 25 September (12h30 - 14h00)


The artificial intelligence in the Health - Our experience as a research Laboratory in Northeast of Brazil

Federal University of Rio Grande do Norte (UFRN) - ( - )

Abstract: Dengue is recognized as a health problem in tropical countries. Monitoring and control of Aedes Aegypti is one of the effective actions that can be used to deal with dengue outbreaks. A useful method of monitoring the aedes vector is by counting ovitrap eggs. The ovitraps are holders where the mosquito can depose its eggs. Counting the eggs deposited in spatially distributed ovitraps can serve as a proxy for levels of aedes infestation. The present work uses a database collected in 397 ovitraps distributed in the municipality of Natal/RN – Brazil. The number of eggs of each studied ovitrap was counted weekly, during the last 4 years (2016 - 2019). Results based on a preliminary analysis suggest that ovitraps data can be informative for the task of dengue cases prediction on the neighborhood of Natal. Four weeks prior to the current week seems to be an acceptable time frame for predicting dengue cases based on ovitraps data.


Strategies for Content Recommendation in the Brazilian Rapid Response to Syphilis Project

Abstract: Syphilis is a Sexually Transmitted Infection (STI) which the Brazilian Ministry of Health has acknowledged an epidemic since 2016. To face such a problem, it is essential to develop and implement educational actions enhanced by information and communication technologies to qualify, train and raise awareness nationally. Considering the increasing number of Open Educational Resources developed, existing open health repositories and other digital platforms that allow interaction in the Brazilian Unified Health System (SUS) as well as the vast number of Healthcare Information Systems, it is essential to develop solutions to efficiently recommend content according to the interest of health professionals and the current needs and priorities of the SUS, such as the epidemic of syphilis. We present a discussion on the information systems and strategies of recommendation systems based on this scenario, integrating health surveillance, formative needs, georeference of health teams and professionals and epidemiological data to recommend content to health professionals all over the country.


The artificial intelligence in the Health - Our experience as a research Laboratory in Northeast of Brazil

Abstract: Greater availability and access to information and communication technologies have formed a more "connected" society. It provides more interactions between people. Also, it fosters technology-driven Distance Education (DE). In this way, new methodologies have been developed to improve teaching and learning in DE, such as artificial intelligence methods. The main objective of this work is proposes an association between artificial intelligence techniques and any one student’s feature. We use, in first moment, the concepts of Learning Styles (LS) like a student’s feature. These concepts identify the learning preferences of each student. It aims at responding the following questions: Is it possible, in an automatically way, to identify the students' LS from their interactions with the Learning Management System (LMS)? What techniques could be developed to identify the LS of the course students conducted in the DE modality, so that it will improve a better academic way to student's learning? In order to answer these questions, we used some artificial intelligence algorithms to identify the relation of the students’ LS with their behaviors in LMS. Results show a low relation of the LS of the students associated with their behaviors in LMS. However, this process identified a new category of LS - it is called indefinite. It corresponds to students without preference for any of the other classifications of LS identified.

Call for papers


An alternative keyboard for communication of patients with amyotrophic lateral sclerosis

Presenter.Ph.D. in Biosystems Engineering, currently Bachelor in Information Technology at UFRN and Resident Researcher at LAIS. Laboratory of Technological Innovation in Health (LAIS), UFRN, Natal, Brazil


Artificial Intelligence applied in a Human-Machine Interface for an alternative communication system to ALS patients

Presenter: The author are Biomedical Engineering undergraduate students at UFRN and Researchers at LAIS. Laboratory of Technological Innovation in Health (LAIS), UFRN, Natal, Brazil.


Computer Vision and AI applied to blink detection for communication interface for ALS patients

Presenter: Computer Science undergraduate student at UFRN. Currently researching Deep Learning approaches on Natural Language Processing and Computer Vision tasks. Also interested in studying Algorithms and Data Structures. Laboratory of Technological Innovation in Health (LAIS), UFRN, Natal, Brazil


Company Session

11.45 - 12.00

Federal University of Rio Grande do Norte (UFRN)
Ricardo Alexsandro de Medeiros Valentim, PhD in Electrical and Computer Engineering