A point rarely taken into consideration regarding clinical data management involves its possible use for scientific research. Beyond the ethical questions related to the ownership and anonymization of personal data, research activities present particular challenges regarding data management, not only when they are heterogeneous and come from different sources but also when they are multicentric (that is, produced by different centers or institutions). To address these issues we designed an integral system for the management of clinical information and biomedical signals in order to deal with the great amount of data from those sources associated with the research projects of our lab. DataNing is a system that provides efficient access to information, facilitating analysis to collaborating researchers.



Keywords: Clinical information, Databases, Biomedical signals.
Team: Camila Reinaldo, Gianfranco Bianchi, Oscar Filevich, Daniela S. Andres
Paper:
1- Reinaldo, Camila; Bianchi, Gianfranco; Wilken, Miguel & Andres, Daniela S. (2020). “Accelerometry signals’ recording protocol and database for the quantitative diagnosis of Parkinson’s disease” Revista Argentina de Bioingeniería, 24(5), 67–76.

This line of work lies within the field of Social Studies of Science and Technology (STS) and is geared to an inquiry into the local scientific field, and more specifically on teams dealing with research of applied technologies. The goal is to understand in which ways the working team of a Neuroengineering lab conceives and undertakes processes of technological transfer as well as the mechanism deployed in order to further said objective. From an ethnographic approach, we analyze the meanings mobilized and the modalities of linkage established by the members of the Lab, in order to turn technological advances into products used by target communities.



Keywords: Anthropology of science and technology, STS Studies, Laboratory Ethnographies, Linkage and Technology Transfer.
Team: Rodrigo Ruiz Menna, María Soledad Córdoba, Francisco Rosso.
Paper:
1- Córdoba, M. Soledad y Azcurra Karen (2021) “Ciencia tomada. Estrategias frente al desfinanciamiento (2016-2019)”, en Ciencia, Tecnología y Política, Vol. 4, Nr. 7, pp. 67-76.
2- Hernández, Valeria y Córdoba, M. Soledad (2018) “Laboratorización del mundo: escenarios contemporáneos de la ciencia y la tecnología”, en Etnografías contemporáneas, vol. 4, nº 6, pp. 7-18.
3- Hernández, Valeria y Córdoba, M. Soledad (2018) “De la cancha al laboratorio. Trayectoria del investigador que logró clonar los mejores caballos de polo de la Argentina”, en Etnografías contemporáneas, vol. 4, nº 6, pp. 109-123.
4- Córdoba, M. Soledad; Buccellato, Marcos; Bilañski, Giselle; Smal, C.; Guzzo, Dante y Azcurra, Karen (2018) “Sobre mercancías, redes e imaginarios. Reflexiones a partir de un diálogo interdisciplinario en torno al quehacer científico local”, en Etnografías contemporáneas, vol. 4, nº 6, pp. 77-108.

Project Aire Fresco: Breathing Panorama is an artistic installation created based on an interactive experience that directly involves participants through the visualization of their breathing patterns. This is achieved through the imaging of a native forest that reflects the collective biodiversity of the inhabitants of LatinAmerica. This multidisciplinary project is in the crossroads of botanics, medical physiology, programming, technology and visual arts.



Keywords: Art, Fractal geometry, Native flora, Respiratory physiology.
Team: Federico Parra, Nahuel Giménez, Nicolás Tentoni, Teresa Politi, Gabriel Noel.
Partners: Hernán Pitto Bellochio y Escuela de Arte y Patrimonio (UNSAM).

Pediatric patients with complex medical conditions (CMC) face a meaningful risk of complications if indications from medical personnel are not thoroughly followed. This indications may include special care procedures, such as manipulation of tracheostomies, other ostomies, handling of nasogastric tubes and care of chirurgical wounds, among others. In this context, caretakers frequently confront considerable obstacles including elevated levels of stress, lack of confidence in their abilities and difficulties to remember or interpret written instructions. This situation is aggravated when combined with the emotional commitment involved in the patient’s care, influencing both the health of the patient as well as the psychological welfare of the caretakers. This project aims to develop and evaluate an app with Artificial Intelligence (AI) destined to the caretakers of pediatric patients with CMC, comparing its effectiveness with two other modes of assistance: traditional and an app without AI.



Keywords: congenital cardiopathies, complex medical Conditions, artificial intelligence, large language models, care, adherence, caretaker stress.
Team: Victoria Belén Molina, María Sol Sayago, María Otero, Maite Filmus, Gianfranco Bianchi, Teresa Politi, Gabriel D. Noel, Daniela S. Andrés, Mariana Origone, Pablo Genera, María Elisa Azcárate.
Partners: Hospital Garrahan and University of California Los Angeles (UCLA).

Several conditions with a neurological origin, including general communication disorders but also specific afflictions related with language and its articulation, prevent those persons affected by them to produce linguistic emissions in a competent fashion. Even when these people may interpret, understand and react properly to oral instructions, their incapability of responding in a similar way and of initiating conversational intercourse presents a hurdle to their capability of socializing, bringing a huge handicap to their quality of life. Furthermore, in the case of children, this kind of affliction also affects their normal social and affective development. In order to help these people we created BICOM, a customizable communicator based on easy to recognize images that its users can adapt and mobilize in order to complement or substitute natural language articulation. Images can be edited and created by the users themselves, from photos, videos, or images downloaded from the web. The app works through an AI engine in order to propose new content and expressions to the user, amplifying their communication possibilities. Moreover, it allows for free association of terms in multiple categories, either created by the user according to their need or proposed by the app itself, in order to extend the use of semantic networks.



Keywords: neurodevelopment, language disorders, artificial intelligence, large language models, digital communicator.
Team: Delfina Espelet, Violeta Merande, Gabriel D. Noel, Daniela S. Andrés, Mariana Origone, Pablo Genera, María Elisa Azcárate.

Even when the diagnosis of ischemia or acute myocardial infarction (AMI) relies on a battery of analyses in specialized centers, a single precordial channel of EKG allows for early detection of an undergoing ischemia. Using artificial intelligence tools, we designed a system that allows for automatic diagnostic through a mobile application of the risk of being undergoing AMI, for prompt derivation of patients in a life-threatening condition. As a proof-of-concept for the device, we have developed a neural network that recognized EKG signals with pathologies in the ST segment or T-wave, characteristic of AMI. Our algorithm detects the cardiac cycle and using a pattern-recognition neural network it detects the presence of AMI with 99% accuracy.



Keywords: Acute myocardial infarction , Artificial neural networks, Artificial Intelligence (AI), Life-threatening conditions.
Team: Federico Alscher, Rocío Wegman, Sol Sayago, Gianfranco Bianchi, Teresa Politi, Gabriel D. Noel, Sabrina S. Andrés
Partners: Instituto Cardiovascular Buenos Aires y Quanttrace.

Congenital cardiopathies are complex pathologies characterized by the presence of anatomical anomalies of the heart at the moment of birth. Such anomalies are highly variable, both anatomically and physiologically. For this reason, even when they may be corrected through cardiovascular surgery, every procedure must be designed on a personalized basis by the medical and technical staff. In order to carry out the surgical planning, the professional team of the Service of Cardiovascular Surgery of Hospital Garrahan uses mathematical tools that allow calculation and prediction of hemodynamic variables such as resistance, flow and pressure, before and during surgery. The main goal of this project is to develop a mobile app that may allow for simulation, through simple equations of fluid mechanics, the hemodynamic conditions of the heart in physiological conditions and under complex cardiopathies.



Keywords: Congenital cardiopathies, Computational simulation, Poiseuille Law, Pediatric cardiovascular surgery.
Equipo: Teresa Politi, Rocío Wegman, Sol Sayago, Gabriel D. Noel, Sabrina S. Andrés, Mariana Origone, Pablo Genera, María Elisa Azcárate.

Aortic valve replacement is currently one of the most common cardiovascular interventions. Prosthetics valvular dysfunction is one of the most prevalent complication in the median and long term follow up. One of the hemodynamic factors linked to prosthetic valvular dysfunction is blood turbulence. In this line of work we aim to evaluate the presence of blood flow turbulence in the clinical and echocardiographic follow up of patients with aortic valve replacement. We additionally aim to analyze the relationship between blood turbulence and the presence of prosthetic valve dysfunction. Our working hypothesis is that blood flow turbulence contains valuable information regarding the hemodynamic conditions surrounding the prosthetic valve and may possibly be associated with prosthetic valve dysfunction.



Keywords: Cardiac valves, Aortic stenosis, Valvular replacement, Turbulence, Doppler echocardiography.
Team: Azul Giraud, Tomás Mendivil, Teresa Politi, Daniela S. Andres
Partners: Cardiovascular Institute Buenos Aires (ICBA), British Hospital, Institut Jean Le Rond D’Alembert - Sorbonne Universités
Paper:
1- Cerminati, Andrea; Politi, M. Teresa; Andres, Daniela S. (2025) “Quantification of blood flow complexity from carotid doppler ultrasonography: perspectives for atherosclerotic risk”, Cardiology doi: 10.1159/000547437.

The Frank-Starling Law establishes the basis of the influence of the end-diastolic volume in the development of the contractile strength in the heart. This active tension-length phenomenon depends on the molecular elements of the muscular fiber which are responsible for these contractile properties. Even when they are of capital importance for cardiac physiology, the relationship between the molecular mechanisms of contraction of the muscle fiber and the cardiac contractility curve or active tension are still poorly understood. Even when mathematical models of chemical kinetics have been proposed in order to help understand the Frank-Starling mechanism, such models rely on a large number of equations, making both analytical treatment and numerical integration extremely difficult. To these ends we are working in chemical kinetics models leading to a better understanding of the fundamental properties of the molecular mechanisms underlying Frank-Starling Law, in order to facilitate their treatment and the development of potential clinical applications.



Keywords: Frank-Starling Law, Cardiac contractility, Molecular mechanisms of muscular contraction, Computational simulation, Chemical kinetics
Team: Camila Ureta, Teresa Politi, Daniela S. Andres.