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  • Artificial Intelligence for COVID-19 chest X-ray diagnosis

    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”.

     

    Source: Técnico

  • New Book by the INESC-ID researcher Andreas Wichert and his PhD student Luís Sá-Couto

    New Book by the INESC-ID researcher Andreas Wichert and his PhD student Luís Sá-Couto

    World Scientific just published the work “Machine Learning — A Journey to Deep Learning”, written by INESC-ID researcher Andreas Wichert and  his PhD student Luís Sá-Couto.

    This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.

    The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.

    The book is available here.

     

    About the authors:

    Andreas Wichert studied computer science at the University of Saarland, where he graduated in 1993. Afterwards, he became a PhD student at the Department of Neural Information Processing, University of Ulm. Since 2006 he is Assistant Professor at Department of Computer Science and Engineering, University of Lisbon where he is as well lecturing about machine learning and quantum computation. His research focuses on neuronal networks, cognitive systems and quantum computation.

    Luis Sa-Couto studied computer science at the Department of Computer Science and Engineering, University of Lisbon, where he graduated in 2018. Since then he is a PhD student under the supervision of Prof Andreas Wichert with the topic Extending Deep Learning Applicability Through Attention-inspired Networks for Object Recognition. He lectured practical classes in AI and machine learning.

  • COVID-19 detection from coughs and speech

    COVID-19 detection from coughs and speech

    A team of researchers from IST (Instituto Superior Técnico – Universidade de Lisboa) and INESC-ID (Instituto de Engenharia de Sistemas e Computadores – Investigação e Desenvolvimento), coordinated by Isabel Trancoso, is developing a new project to explore the possibility of automatically detecting COVID-19 from its effects on cough and speech.

    This project would allow developing a cheap, fast and easy to use artificial intelligence-based tool (deployed as a web platform and/or a mobile application) that could provide a preliminary assessment of potential infection by COVID-19. Although not a clinical diagnosis, this is valuable information that would help individuals to adopt preventive measures, and public and private healthcare operators, institutions, companies, etc. to optimize their screening campaigns by allowing them to focus their attention on suspected infected individuals.

    For this goal, it is fundamental to collect an extensive dataset with representative examples of speech and simulated coughs and snores from both COVID-19 positive (symptomatic and asymptomatic) and negative individuals (ideally including also participants with respiratory conditions other than COVID-19, such as flu, cold, asthma, etc.). Then, signal processing and machine learning techniques will be used to assess the presence of biomarkers indicative of COVID-19 in coughs and speech, and to develop robust systems for the detection of COVID-19.

    “We hope that this work will not end with the current pandemic and will allow us to continue studying clues of diseases that affect the respiratory system through acoustic signals that can be collected in a non-intrusive way”, said Isabel Trancoso, The Project Coordinator.

    Your participation in this study is essential and warmly appreciated. To participate, just follow this link (where you can find the informed consent form), or use the following QR code.

    More info: https://www.hlt.inesc-id.pt/w/COVID19

  • Arlindo Oliveira is one of the new members of STOA International Advisory Board

    Arlindo Oliveira is one of the new members of STOA International Advisory Board

    Arlindo Oliveira, President of INESC and Researcher at INESC-ID was invited to be one of the new members of the STOA (European Parliament Panel for the Future of Science and Technology) Advisory Board.

    “The European Parliament panel for the future of science and technology will define and propose, to the Parliament and to the Commission, the policies and strategies that will be adopted in Europe, for a number of key digital technologies, including Artificial Intelligence, Quantum Computing and Nanotech. It is to me an honor to have been invited to the advisory board of this panel, which will play a significant role in the definition of the key choices and includes a number of people with an enormous experience in the development and adoption of transforming technologies”, said Arlindo Oliveira.

    The also distinguished professor of Instituto Superior Técnico is now part of the list of world-renowned individuals, including personalities from academia, international organisations, the private sector, civil society and think tanks. During the 2020-2024 mandate, the Board will focus in particular upon STOA activities in the area of artificial intelligence (AI), including its Centre for AI (C4AI).

    List of STOA International Advisory Board members (2020-2024 mandate)

     

    About Arlindo Oliveira

    Arlindo Oliveira is a distinguished professor of Instituto Superior Técnico, with the Department of Computer Science and Engineering. He obtained a PhD from UC Berkeley in 1994, under a Fulbright fellowship, after a BSc and a MSc from IST, in 1986 and 1989, respectively. His major areas of interest are Algorithms and Complexity, Machine Learning, Bioinformatics and Digital Circuit Design. He has worked at CERN, Cadence Laboratories and INESC-ID. He is a member of the Portuguese Academy of Engineering and a senior member of IEEE.

  • Nine INESC-ID researchers are among the most cited top scientists in the world

    Nine INESC-ID researchers are among the most cited top scientists in the world

    Nine INESC-ID researchers are among the most cited top scientists at the top 2% of their respective areas.

    Portugal is represented in this list compiled by Stanford University with 385 scientists affiliated to several national institutions.

    The rankings are based upon a researcher’s citations for both a single year (2019) and cumulative across their careers. Titled “Updated science-wide author databases of standardized citation indicators,” the list uses algorithms that quantify and systematically rank individuals into consistent scientific fields.

    The scores are provided both with and without self-citations to lessen the impact of researchers employing extreme self-citations or the use of citation farms (small clusters of researchers massively citing each other’s work).

    Ranked within the careerlong citation impact list are these INESC-ID researchers:

    The article and list of leading scientists can be consulted at: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000918

  • João Madeiras Pereira is a new senior member of ACM

    João Madeiras Pereira is a new senior member of ACM

    João Madeiras Pereira was nominated Senior Member of the ACM – Association for Computing Machinery.

    As mentioned by the Senior Member Committee “we are delighted that you will be among the inductees honored with this designation and wish to congratulate you on this well-deserved recognition”.

  • INESC-ID President Inês Lynce is also the new National Co-Director of CMU Portugal Program

    INESC-ID President Inês Lynce is also the new National Co-Director of CMU Portugal Program

    Inês Lynce was appointed on January 27th as co-director of the CMU Portugal Program by Fundação para a Ciência e Tecnologia (FCT). The Associate Professor with habilitation at Instituto Superior Técnico and Presidente of INESC-ID assumes the national co-direction of the international partnership alongside Nuno Nunes, replacing Rodrigo Rodrigues who has been in office since the renewal of the Program in 2018.

    According to the newly appointed co-director, “It is with great pleasure and some expectation that I assume this position. I have been connected to the CMU Portugal Program for several years as a researcher, having already belonged to the team of several projects supported under the Program. Now the commitment will be entirely different and focused on helping the partnership to achieve its strategic goals by 2023 ”. “Personally, I am honored to have been appointed to this position and join such a prestigious and dynamic team with remarkable results achieved in recent years,” she says.

    Inês Lynce, who will be the first woman to lead the CMU Portugal Program, is highly recognized for her work in the field of Artificial Intelligence, namely in the area of ​​problem solving with restrictions and optimization. Her main contributions refer to the development of algorithms and computational tools and their application to solve practical problems as diverse as developing timetables in universities, software package upgradability, the functioning of biological networks and the automatic creation of programming code from examples.

    Since 2021, she has been a member of the Editorial Board of the prestigious scientific magazine “Journal of Artificial Intelligence Research” and is a recurring member of international conferences committees on Artificial Intelligence. This year she will be also part of the “Women in Science” initiative, promoted by Ciência Viva, the National Agency for Scientific and Technological Culture.

    Inês Lynce is also the President of INESC ID, the Portuguese research center for combined Computer Science/Engineering (CSE) and Electrical and Computer Engineering (ECE), a role she assumed last year and where she already was a senior researcher.

  • IObundle IP at 2020 Design&Reuse top10

    IObundle IP at 2020 Design&Reuse top10

    IOb-SoC is a System-on-Chip template equipped with a CPU, a memory system and a serial communications module. By democratising the use of CPUs in electronic design, IOb-SoC is at the forefront of enabling powerful AI and machine learning algorithms in all sorts of electronic equipments, especially ultra low-poer ones. Users can easily customise IOb-SoC to implement more complex and specific SoCs. It uses RISC-V processors at its core, dispensing with cumbersome and expensive solutions such as ARM processors. By democratising the use of CPUs in electronic design, IOb-SoC is at the forefront of enabling powerful AI and machine learning algorithms in all sorts of electronic equipment, especially ultra-low-power ones. It is released in the public domain under the MIT permissive license and distributed using the Github platform. By providing the code publicly, and at no charge, stakeholders can easily use IOb-SoC for teaching, research, and industrial innovation.

    The motivation for IOb-SoC is that of a speedy and straightforward setup, quickly grasped by students, instructors, researchers and innovators. The IOb-SoC hardware uses the System Verilog language, and its software uses the C/C++ languages.

    The design is straightforward: the processor reads instructions and accesses data from the memory system and peripherals, and executes the program. The system has been used in several master’s dissertations and is being used in one PhD work, supervised by our researcher José Teixeira de Sousa.

    IOb-SoC has also been used as a research tool and industrial applications.

  • Alumnus Paulo Martins received the Cor Baayen Young Researcher Award

    Alumnus Paulo Martins received the Cor Baayen Young Researcher Award

    

Paulo Martins was awarded an honorable mention "Cor Baayen Young Researcher Award", by the European Research Consortium for Informatics and Mathematics (ERCIM).

Paulo Martins finished his PhD in 2019 "Arithmetic and Algorithms for Emerging Cryptography" under the guidance of Leonel Sousa at INESC-ID and currently holds positions at Samsung R&D Institute United Kingdom. He was one of the distinguished in a total of 13 finalists of this special award, which annually recognizes the promising work developed by a young researcher in the fields of computing and mathematics.

Paulo Martins revealed that the distinction surprised him, since this is a “very competitive prize”. “I see this mention as a validation of my doctoral thesis and cause for enthusiasm for future work”, he says. Emphasizing the importance of the award “in the area of ​​computer science and applied mathematics”, Paulo mentions that he has “a special appreciation for this contest” since its founder “stimulated research in the area of ​​cryptography, which is one of my main research interests ”.
  • Researchers team on top 5 in International Timetabling Competition

    Researchers team on top 5 in International Timetabling Competition

    The 4th edition of the International Timetabling Competition took place during the last year and brought together researchers and enthusiasts from 57 countries to solve complex scheduling problems.

    From all the participants, only 15 teams managed to solve the competition instances, among which is a team of Portuguese researchers from IST / INESC-ID. The team composed by the Ph.D. student Alexandre Lemos, and Professors Pedro Monteiro and Inês Lynce, managed to collect 79 points and reach a place on top 5.

    The great challenge of this competition was to schedule the timetables of large universities with different characteristics and restrictions. The competition instances were obtained from 10 different universities from 9 different countries spread across 5 continents. The competition is now over, however, the work goes on and the results are continuously compared within the scientific community on the competition website.

    The ITC 2019 ranking can be consult here.