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Automated Disease Triage for the Real World

Grant number: 19/05018-1
Support Opportunities:Scholarships abroad - Research
Start date: August 15, 2019
End date: June 29, 2020
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Eduardo Alves Do Valle Junior
Grantee:Eduardo Alves Do Valle Junior
Host Investigator: Matthieu Cord
Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Institution abroad: Université Paris-Sorbonne (Paris 4), France  

Abstract

Our main goal is to advance the state of the art in computer-aided diagnosis. We will focus on two diseases - melanoma, and diabetic retinopathy - but we expect that the techniques developed will generalize to a wide range of possible image-based diagnostics. Automated triage/screening offers a promising solution to the disparity between available healthcare professionals and increasing incidence of degenerative diseases in an aging population. Automated triage/screening is a valuable resource for primary health care professionals: nurses and general practitioners, assisting them in the difficult decision of who should be referred to the specialist doctor, and among those referred, which cases are the most urgent.

News published in Agência FAPESP Newsletter about the scholarship:
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Articles published in other media outlets ( ):
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Scientific publications (6)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
DE OLIVEIRA, EDUARDO; BINDA, JOMARA; VALLE, EDUARDO; LOPES, RENATO. Paperclickers: Affordable solution for classroom response systems. COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, v. 28, n. 6, p. 16-pg., . (19/05018-1)
VALLE, EDUARDO; FORNACIALI, MICHEL; MENEGOLA, AFONSO; TAVARES, JULIA; BITTENCOURT, FLAVIA VASQUES; LI, LIN TZY; AVILA, SANDRA. Data, depth, and design: Learning reliable models for skin lesion analysis. Neurocomputing, v. 383, p. 303-313, . (19/05018-1, 17/16246-0)
BISSOTO, ALCEU; VALLE, EDUARDO; AVILA, SANDRA; IEEE COMP SOC. Debiasing Skin Lesion Datasets and Models? Not So Fast. 2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2020), v. N/A, p. 10-pg., . (13/08293-7, 17/16246-0, 19/05018-1)
DE OLIVEIRA, EDUARDO; BINDA, JOMARA; VALLE, EDUARDO; LOPES, RENATO. Paperclickers: Affordable solution for classroom response systems. COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, . (19/05018-1)
RIBEIRO, VINICIUS; AVILA, SANDRA; VALLE, EDUARDO; IEEE COMP SOC. Less is More: Sample Selection and Label Conditioning Improve Skin Lesion Segmentation. 2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2020), v. N/A, p. 10-pg., . (17/16246-0, 19/05018-1)
DOUILLARD, ARTHUR; VALLE, EDUARDO; OLLION, CHARLES; ROBERT, THOMAS; CORD, MATTHIEU; IEEE COMP SOC. Insights from the Future for Continual Learning. 2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGITION WORKSHOPS (CVPRW 2021), v. N/A, p. 10-pg., . (19/05018-1)