I am a researcher at INESC-ID, Lisbon. I hold a Master’s degree in Biomedical Engineering, NOVA School of Science and Technology (FCT NOVA). I am particularly interested in the application of statistical and machine learning methods to clinical data. I've been developing my work in the context of medical image processing, image segmentation and quantification, analysis of high-dimensional clinical data and machine learning and biostatistics for personalized medicine.
WORK EXPERIENCE
January 2020 -
Researcher at INESC-ID
"PREDICT - Personalized therapy for RhEumatic Diseases"
Funding: Portuguese Foundation for Science and Technology (PTDC/CCI-CIF/29877/2017)
January 2019 - November 2019
Master thesis student at Nuclear Medicine-Radiopharmacology research group
Champalimaud Centre for the Unknown, Champalimaud Foundation
January 2017 - February 2017
Curricular internship at the Nuclear Medicine-Radiopharmacology clinical service
Champalimaud Centre for the Unknown, Champalimaud Foundation
EDUCATION
Sep. 2014 - Nov. 2019
Integrated Master in Biomedical Engineering,
NOVA School of Science and Technology (FCT NOVA)
Final classification: 17/20
MSc Dissertation: "Reproducibility study of tumor biomarkers extracted from Positron Emission Tomography images with 18F- Fluorodeoxyglucose", http://hdl.handle. net/10362/91156
Sep. 2017 - Feb. 2018
ERASMUS+ program, Biomedical Engineering,
Politecnico di Milano, Italy
PUBLICATIONS
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Constantino, C., Carvalho, A. M., Vinga, S. (2020) Sparse consensus classification for discovering novel biomarkers in rheumatoid arthritis. In: Machine Learning, Optimization, and Data Science. LOD 2020. Lecture Notes in Computer Science. (Accepted)
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Constantino, C. S., Oliveira, F. P. M., Silva M., Oliveira, C., Castanheira, J. C., Silva, Â., Vaz, S. C., Vieira, P., Costa, D. C. (2020) Reproducibility study of lesion features extracted from 18F-FDG PET/CT images acquired on analog and digital PET/CT scanners. European Journal of Nuclear Medicine and Molecular Imaging. (Submitted)
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Constantino, C. S., Oliveira, F. P. M., Silva M., Oliveira, C., Castanheira, J. C., Silva, Â., Vaz, S. C., Vieira, P., Costa, D. C. (2019) Reproducibility Study of Lesion Features Extracted from 18F-FDG PET Images of the Same Patients Acquired on Two Philips PET/CT Scanners: Digital VEREOS versus GEMINI TF. In: Annual Congress of the European Association of Nuclear Medicine October 12 – 16, 2019 Barcelona, Spain. Eur J Nucl Med Mol Imaging 46, S771 (2019). DOI: 10.1007/s00259-019-04486-2
ORAL COMMUNICATIONS
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Constantino, C., Carvalho, A. M., Vinga, S. (2020) Sparse consensus classification for discovering novel biomarkers in rheumatoid arthritis. Machine Learning, Optimization, and Data Science (LOD 2020), Siena, Italy, July 19-23
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Constantino, C. S., Oliveira, F. P. M., Silva M., Oliveira, C., Castanheira, J. C., Silva, Â., Vaz, S. C., Vieira, P., Costa, D. C. (2019) Segmentação automática de lesões ávidas para FDG em PET/CT baseada numa técnica de clustering bayesiana. Congresso Nacional de Medicina Nuclear, Porto, Portugal, November 28-30
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Constantino, C. S., Oliveira, F. P. M., Silva M., Oliveira, C., Castanheira, J. C., Silva, Â., Vaz, S. C., Vieira, P., Costa, D. C. (2019) Extração de características de lesões ávidas para FDG: estudo da reprodutibilidade entre Philips Vereos Digital e GEMINI TF16 PET/CT. Congresso Nacional de Medicina Nuclear, Porto, Portugal, November 28-30
CONTACT
Instituto de Engenharia de Sistemas e Computadores - Investigação e Desenvolvimento,
R. Alves Redol 9, 1000-029 Lisboa