Artificial Intelligence for COVID-19 chest X-ray diagnosis
The DeepPathCOVIDx project will allow to develop of a solution that will assist healthcare professionals in the analysis of chest X-ray images.
A team of researchers from Técnico and INESC-ID, in collaboration with Hospital da Luz Learning Health, is developing a solution consisting of AI models for the analysis of chest radiography of patients suspected of having COVID-19, in an emergency context.
Besides causing cough, fever and fatigue, the SARS-CoV-2 virus can cause acute upper tract infection. Identifying these clinical cases and prevent worsening clinical conditions is crucial to reduce pandemic deaths. Conventional chest radiography allows the assessment of infection and, consequently, the strategy of monitoring and treating the patient. Chest X-rays can also be used as a complementary diagnostic method, although they are not part of the official protocol.
Thus, the creation of AI models to identify radiological characteristics of COVID-19 in chest X-ray images allows, together with other clinical information, to help in the decision-making for suspected cases of COVID-19, being an important and useful tool to support the work of healthcare professionals. “The main purpose of this tool is to be able to detect, autonomously, and with a high degree of certainty, COVID-19 on chest X-rays and how severe the disease is”, explains Arlindo Oliveira, Técnico professor and Principal Investigator of the project.
This tool aims to optimize the work of radiologists, identifying and prioritizing the x-rays of suspected COVID-19 patients in the work list, to assist doctors in an emergency context when radiologists are not available, with a tool for analyzing radiographs, and to increase efficiency in an emergency context, facilitating professionals’ decision making.
The system is currently being tested “with data from Hospital da Luz and Hospital Beatriz Ângelo”, shares by professor Arlindo Oliveira. “The data provided by our partners will allow us to test the accuracy of the model. If we succeed, it will be included in hospital admissions”, explains professor Arlindo Oliveira.
The project’s feasibility study should be completed in a few months. The next phase will go through the implementation of the tool in a hospital. Although this phase no longer relies on the research team, professor Arlindo Oliveira believes that “it may be operational a few months after the demonstration is finished”.
The multidisciplinary team consists of Técnico/INESC-ID researchers in the fields of machine learning and artificial intelligence, radiologists, ER doctors at Hospital da Luz Lisboa and Hospital Beatriz Ângelo, human factors and ergonomics experts, information systems experts and managers. DeepPathCOVIDx was one of the projects funded bythe Portugal 2020 programme. The results will be announced in the first half of this year.
According to professor Arlindo Oliveira “the collaboration between engineering and medicine is always very fruitful and will play an essential role in medical advances”.
Workshop Metabolism and mathematical models: Two for a tango
Dates: November 18-19, 2021
Location: This workshop will be held in a virtual way
The topic of this workshop is metabolism in general, with a special focus, although not exclusive, on parasitology. Besides an exploration of the biological, biochemical and biomedical aspects, the workshop will also aim at presenting some of the mathematical modelling, algorithmic theory and software development that have become crucial to explore such aspects.
This workshop is being organised in the context of two projects, both with the Inria European Team Erable. One of the projects involves a partnership with the University of São Paulo (USP), in São Paulo, Brazil, more specifically the Institute of Mathematics and Statistics (IME) and the Institute of Biomedical Sciences – Inria Associated Team Capoeira – and the other involves the Inesc-ID/IST in Portugal, ETH in Zürich and EMBL in Heidelberg – H2020 Twinning Project Olissipo.
The workshop is open to all members of these two projects but also, importantly, to the community in general.