The Tech4Medics research center will participate in the VI CICA Scientific Conference, Faculty of Medicine, University of Chile, to be held on July 9, 2026, with the presentation of six scientific posters. These contributions showcase ongoing research led by students, researchers, and collaborators, highlighting the center’s commitment to the development of Artificial Intelligence (AI) solutions for medical diagnosis, biomedical image analysis, and clinical decision support.
This milestone reflects the interdisciplinary nature of Tech4Medics, bringing together expertise from engineering, computer science, medicine, and health sciences to develop innovative technologies with the potential to improve healthcare delivery and patient outcomes.
Prediction of Aortic Stenosis Severity from Baseline Electrocardiograms Using Artificial Intelligence
Authors: Aníbal Molina, Cristián Ávila, Alfredo Parra, and Víctor Castañeda.
This work explores the use of artificial intelligence models to estimate the severity of aortic stenosis from baseline electrocardiograms (ECGs), with the goal of supporting early detection and facilitating clinical decision-making.
AI in Breast Imaging: Validation of Deep Learning Algorithms for Breast Density Estimation in Mammography and Digital Breast Tomosynthesis
Authors: Daniela Acevedo Fuentes, Cristóbal Gutiérrez Malhue, Denisse Karl Sáez, Carlos F. Navarro, and Víctor Castañeda.
This study evaluates deep learning algorithms for the automated estimation of breast density in mammography and digital breast tomosynthesis, an important imaging biomarker associated with breast cancer risk assessment.
Ultrasound Characterization of Renal Tissue in a Rural Chilean Population Using Artificial Intelligence
Authors: Francisco Romero Muñoz, Catalina Tobar Muñoz, Denisse Karl Sáez, Carlos F. Navarro, Camilo Sotomayor, and Víctor Castañeda.
This research develops AI-based methods for the automated characterization of renal tissue from ultrasound images, aiming to improve kidney disease assessment in underserved rural populations.
Sperm Cell Segmentation and Classification Using a Hybrid Artificial Intelligence Approach
Authors: Camila Maire, Víctor Castañeda, Denisse Karl Sáez, and Carlos F. Navarro.
This project presents a hybrid framework combining image processing techniques and artificial intelligence for the automated segmentation and classification of sperm cells, with potential applications in computer-assisted semen analysis.
Interobserver Variability in Mammographic Anatomical Segmentation for Artificial Intelligence Training
Authors: Benjamín Fuentes Gajardo, Carla Jorquera Díaz, Carolina Bavestrello Ruiz, Carlos F. Navarro, Denisse Karl Sáez, and Víctor Castañeda.
This study investigates how interobserver variability in mammographic anatomical segmentation affects the development and performance of artificial intelligence models, contributing to the creation of more robust and standardized datasets.
Development of Artificial Intelligence Algorithms for Automatic Evaluation of Positioning Criteria in Digital Mammography
Authors: Carolina Bavestrello Ruiz, Denisse Karl Sáez, Carlos F. Navarro, and Víctor Castañeda.
This work focuses on developing AI algorithms capable of automatically assessing positioning quality in digital mammography, supporting quality assurance and improving the consistency of breast imaging examinations.
Together, these six research projects illustrate Tech4Medics’ commitment to advancing artificial intelligence for healthcare. Spanning applications in cardiology, breast imaging, nephrology, reproductive medicine, and medical image analysis, these studies demonstrate the center’s multidisciplinary approach and its strong collaboration among students, clinicians, engineers, and researchers.
The submission of these posters marks an important milestone in preparation for CICA 2026, highlighting the continued growth of Tech4Medics’ research initiatives and its mission to develop innovative AI-driven technologies that contribute to improved healthcare and precision medicine.