Differential cell count in bone marrow aspirates
AI model for cell line counting in bone marrow aspirate samples in collaboration with Hospital 12 de Octubre (Spain).
Digital tools to support the development of a new oral treatment for visceral leishmaniasis
NEGLECTED TROPICAL DISEASES
Digital microscopy quality control and AI models for diagnosis and quantification of visceral leishmaniasis. With DNDi, FIND, Kenya Medical Research Institute (Kenya), University of Gondar (Ethiopia) and Instituto de Salud Carlos III (Spain).
Florence: An intelligent assistant to support clinical decision making in the point-of-care
An intelligent assistant to support screening and diagnostics working on smartphones based on large language models (LLMs) and multi-modal edge-AI. Supported by Bill & Melinda Gates Foundation.
Ada: an AI assistant to help hematologists.
An intelligent assistant integrated with our case management platform to support hematologists.
Diagnosis and quantification of filariae
NEGLECTED TROPICAL DISEASES / Parasitology
AI system for real time detection and classification of filarial species in blood samples with limited connectivity . Developed in collaboration with Instituto de Salud Carlos III (Spain).
Detection and quantification of geohelminths
NEGLECTED TROPICAL DISEASES
AI model for the identification and quantification of helminth eggs (Trichuris trichiura, Ascaris lumbricoidesand hookworms) in stool samples together with Kenya Medical Research Institute (Kenya).
Predictive models for leukemia
Development of predictive models for treatment response in acute myeloid leukemia (AML) from multiple data sources. In collaboration with Hospital 12 de Octubre.
Myelodysplastic syndromes Diagnostic and Prognostic Algorithms
Development of AI models for diagnosis and prognosis of myelodysplastic syndromes (MDS). In collaboration with Hospital Clínico San Carlos.
Characterization of hematopoietic disorders of the erythroid lineage
Characterization of the terminal erythroid differentiation (TED) by artificial intelligence through analysis of bone marrow microscopy images, in collaboration with Hospital Vall d´Hebrón.
Cerebrospinal fluid cell counts for meningitis in newborns
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.
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.
Digital tools to support clinical routine and decision making in hematology departments
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.
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).
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).
RetiSpot: fundus digitalization
Portable, 3D-printed, smartphone-controlled retinograph connected to a telemedicine web platform for the screening of fundus lesions. With Centro de Investigación en Saúde de Manhiça (Mozambique) and Institut Català de Retina, ISGlobal, the UPM (Spain).
TiraSpot: RDT universal reader
An universal AI algorithm capable of interpreting the result of any rapid test up to 3 bands and sending the information to a monitoring platform.
Epidemic monitoring platform for Covid RDT.
AI model and epidemiological platform for reading and recording 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).
AI Workshops & Challenges
Our technology and methodology allows us to run AI workshops and diagnostic competitions for professional training and scientific dissemination. At the XII SEMTSI congress, SpotLab organised a workshop on AI in microbiology and the Tropical Medicine Challenge.