We help you create your AI algorithm based either on your data or new images acquired with our devices. Full solutions can be deployed in our easy-to-use web and smartphones (edge-AI) or you can deploy the AI models in your own infrastructure. Full solutions can be deployed in our easy-to-use web and smartphones (edge-AI) or you can deploy the AI models in your own infrastructure.
Differential cell count in bone marrow aspirates
Detection and quantification of geohelminths
Neglected Tropical Diseases
Detection and quantification of filariae
Quality control for visceral leishmaniasis
Neglected tropical diseases
Implementation of digital microscopy quality control for the diagnosis of visceral leishmaniasis. Development of an AI model for rapid and accurate diagnosis of visceral leishmaniasis. In collaboration with DNDi, FIND, Kenya Medical Research Institute (Kenya), University of Gondar (Ethiopia) and Instituto de Salud Carlos III (Spain).
Cerebrospinal fluid cell counts
AI model for cell counting and differentiation in cerebrospinal fluid samples from patients with suspected meningitis, in collaboration with the Rabat Children’s Hospital (Morocco), Manhiça Health Research Centre (Mozambique), ISGlobal and Newborn Solutions.
Detection of Onchocerca volvulus
Scanning of subcutaneous nodule samples for detecting Onchocerca volvulus. In collaboration with the Korle-Bu Teaching Hospital (Ghana).
Blood parasite detection
AI model for the detection and quantification of parasites in blood samples, whether for malaria, Chagas disease, leishmaniasis or filariasis. In collaboration with the Universidad Mayor de San Simón (Bolivia), Oswaldo Cruz Foundation – Fiocruz (Brazil), Institute for Medical Research IMR (Malaysia), Fundación Mundo Sano (Argentina) and Instituto de Salud Carlos III (Spain).
Quantification and subtyping of lung lesions
Identification, quantification and characterisation of different COVID-19 lesion patterns in CT images. In collaboration with Hospital Clínic de Barcelona, Clínica Universidad de Navarra, Hospital La Paz and Fundación Jiménez Díaz (Spain).
Quantification of schistosomiasis
AI model for automatic quantification of parasite eggs in stool or urine samples. In collaboration with the University of Berkeley and the Bill & Melinda Gates Foundation.
Bone marrow digitalization
Innovation program for the digitization and analysis of bone marrow samples in the haematology services of more than 10 Spanish hospitals. In collaboration with GSK, Hospital Nuestra Señora de la Candelaria, Hospital Parc Taulí, Hospital Vall d’Hebron, Hospital Miguel Servet, Hospital Peset, etc.
RetiSpot: fundus digitalization
Portable, 3D-printed, smartphone-controlled retinograph connected to a telemedicine web platform for the screening of fundus lesions. In collaboration with the Institut Català de Retina, ISGlobal, Centro de Investigación en Saúde de Manhiça (CISM), (Mozambique) and the UPM.
RDT universal reader
An algorithm capable of interpreting the result of any rapid test up to 3 bands. This model has been tested for several pathologies including: COVID-19, Chagas disease and Cryptococcosis. In collaboration with the Hospital Ramón y Cajal (Spain).
Automatic reading of COVID-19 rapid tests
AI model for reading COVID-19 antigen and antibody tests. In collaboration with the Hospital Ramón y Cajal (Spain).
Quantification of Cryptococcus
Algorithm capable of quantifying the intensity of LFA bands for both the reading of semi-quantitative cryptococcosis tests and their correlation with antigen concentration in qualitative tests. In collaboration with GAFFI (Switzerland), Asociación de Salud Integral (Guatemala) and Instituto de Salud Carlos III (Spain).
Digitization and quality control of rapid Chagas disease tests
Evaluation and comparison of the effectiveness of several LFA for Chagas disease in endemic countries, with the aim of determining the most accurate and reliable LFA in these regions, and storing its results for quality control purposes. In collaboration with FIND (Argentina, Colombia and Bolivia).