Inteligencia artificial. Aplicación en las imágenes cardiovasculares y la prevención cardiovascular
Revista Argentina de Cardiología, 2024
Research interests
I am currently working on the development of artificial intelligence models for the analysis of medical images with the ultimate goal of transferring these tools to the clinical scenario as support systems for different actors in the medical field.
As part of this process, I focus on the validation and analysis of their algorithmic fairness prior to their effective integration with the other components of health information systems. To carry out these tasks I essentially use Python with libraries such as scikit-learn, Keras, PyTorch and django.
In line with this work, we recently published the first open access database of dermatological images collected entirely in Argentina in the ISIC Archive and in the journal Scientific Data. This collective effort was motivated by the need to increase Latin American representation in the databases used in the development of Artificial Intelligence models, which is essential to ensure proper performance of the same in this population.
Recent Work
A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population
Nature Scientific Data, 2023
Introducing Computer Vision into Healthcare Workflows
Digital Health, 2023
Radiomics and Machine Learning for prediction of two-year disease-specific mortality and KRAS mutation status in metastatic colorectal cancer
MEDINFO, 2023
Integrating Dermoscopic Images into PACS Using DICOM and Modality Worklist
MEDINFO, 2023
Towards Unraveling Calibration Biases in Medical Image Analysis
FAIMI, 2023
Towards Unraveling Calibration Biases in Medical Image Analysis
Khipu, 2022
How to ensure fairness in machine learning models for diagnosin illness
Marketplace Tech Radio Interview, 2022
Addressing fairness in artificial intelligence for medical imaging
Nature Communications, 2022
Artificial intelligence in medical images. From theory to application (in Spanish)
delHospital Ediciones, 2021
Bias detection in Machine Learning models for dermoscopy analysis (in Spanish)
Fundación para el Desarrollo Regional, 2022
Data science in healthcare (in Spanish)
Innova Salud Digital, 2021
Experience
2024 - present
Data Scientist
Data Scientist
Health Life Science Studio
Globant, Buenos Aires, Argentina
HLS Data Scientist, Computer Vision, Artificial Intelligence
Facultad de Ingeniería
Universidad de Mendoza, Mendoza, Argentina
Professor of Artificial Intelligence in the Computer Engineering program.
2024 - present
Professor
Professor
2019 - 2024
Researcher and Developer
Researcher and Developer
Artificial Intelligence in Health Program
DIS-HIBA, Buenos Aires, Argentina
Artificial Intelligence, Medical Image Computing, Clinical Decision Support Systems
Group website
Health Informatics Master,
IUHI, Buenos Aires, Argentina
Informatics applied to clinical research, Bioengineering, Big Data, Data Science, Artificial Intelligence
2019 - 2024
Professor
Professor
2018 - 2019
Developer
Developer
Membrane Fusion and Acrosomal Exocytosis Laboratory
IHEM, Mendoza, Argentina
Interface development, Simulation, Data entry, Data Visualization
Education
2020 - present
Doctoral Candidate
Doctoral Candidate
PhD in Engineering
Universidad Tecnológica Nacional, Buenos Aires, Argentina
Advisor: Dr. Rodrigo Echeveste
Co-Advisor: Dr. Enzo Ferrante
Thesis plan: Contributions to translational artificial intelligence: new fair and adaptive machine learning methods for dermoscopies processing in clinical scenarios.
Biomedical Engineer
Universidad de Mendoza, Mendoza, Argentina
Thesis: Design and implementation of a skills training system for minimally invasive surgery
2012 - 2018
Engineering Degree
Engineering Degree
2017
Exchange Student
Exchange Student
Higher Technical School of Telecommunication Engineers
UPM, Madrid, Spain
Academic exchange in the 4th year of the Biomedical Engineering course (Biomedical Imaging itinerary)