Cryptococcosis is a fungal infection that causes serious illness, particularly in immunocompromised individuals such as people living with HIV. Point of care tests (POCT) can help identify and diagnose patients with several advantages including rapid results and ease...
A Smartphone-Based Platform Assisted by Artificial Intelligence for Reading and Reporting Rapid Diagnostic Tests: Evaluation Study in SARS-CoV-2 Lateral Flow Immunoassays
Background: Rapid diagnostic tests (RDTs) are being widely used to manage COVID-19 pandemic. However, many results remain unreported or unconfirmed, altering a correct epidemiological surveillance. Objective: Our aim was to evaluate an artificial intelligence–based...
The Augmented Hematologist: Human-AI Feedback Loops to Assist Differential Cell Count during the Analysis of Bone Marrow Aspirates
Every day, thousands of hematologists worldwide analyze bone marrow aspirate (BMA) samples supported by an optical microscope and their own clinical expertise. A crucial part of the BMA analysis, the differential cell count (DCC), is still a time-consuming task that...
Inteligencia Artificial para salud global: De la digitalización con teléfonos inteligentes a la cuantificación automática de parásitos
Mesa redonda en el XXII Congreso de la Sociedad Española de Parasitología (SOCEPA).
Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT
The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict...
Un sistema de microscopía digital asistido por inteligencia artificial para el diagnóstico de la enfermedad de Chagas
Comunicación oral en el XXV Congreso de la Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica (SEIMC).
Evaluation of a digital system leveraging mobile technology and artificial intelligence for digitalization, remote analysis and supported differential cell count of bone marrow aspirates
BackgroundMicroscopic examination of bone marrow aspirates (BMA) is still, in almost every organization world-wide, a task that is performed with conventional microscopes relying on an in-person diagnostic process. Being these samples left outside the digital world,...
Remote analysis of sputum smears for mycobacterium tuberculosis quantification using digital crowdsourcing
Introduction Tuberculosis (TB) is a leading cause of morbidity and mortality worldwide. Although the development of Xpert MTB/RIF has recently become a major breakthrough, smear microscopy remains the most widely used method for TB diagnosis, especially in low- and...
Telemedicine for international travelers through a Smartphone-based monitoring platform (Trip Doctor®)
Background Overall, more than 50% of international travelers develop symptoms while traveling and 55% of them seek medical assistance during the trip. We conducted a study to evaluate the usefulness of a Smartphone app called TRIP Doctor® to provide telemedicine to...
Artificial Intelligence algorithm for automatic and objective interpretation of the Semiquantitative Cryptococcal Antigen Lateral Flow Assay
Background Higher cryptococcal antigen (CrAg) concentrations are associated with meningitis and death. A novel CrAg semi-quantitative lateral flow assay (CrAgSQTLFA, IMMY, USA) has demonstrated excellent diagnostic performance. However, its visual interpretation...
Una aplicación móvil asistida por inteligencia artificial para el diagnóstico de la filariasis en tiempo real
Comunicación oral en el XII Congreso de la Sociedad Española de Medicina Tropical y Salud Internacional (SEMTSI).
Deep-learning characterization and quantification of COVID-19 pneumonia lesions from chest CT images
A relevant percentage of COVID-19 patients present bilateral pneumonia. Disease progression and healing is characterized by the presence of different parenchymal lesion patterns. Artificial intelligence algorithms have been developed to identify and assess the related...
Combining collective and artificial intelligence for global health diseases diagnosis using crowdsourced annotated medical images
Visual inspection of microscopic samples is still the gold standard diagnostic methodology for many global health diseases. Soil-transmitted helminth infection affects 1.5 billion people worldwide, and is the most prevalent disease among the Neglected Tropical...
Development of an artificial intelligence mobile phone app connected to a telemedicine platform for automatic readout of rapid diagnostic COVID-19 tests
Background Rapid diagnostic tests (RDTs) are being widely used to manage COVID-19 pandemic. We describe the use of a mobile app and an artificial intelligence (AI) readout system for antibody (COVID-Ab) and antigen (COVID-Ag) RDTs connected to a web telemedicine...
Smartphone automatic reading of the CrAg lateral flow assay using an AI algorithm can provide quantitative results
Background The cryptococcal antigen lateral flow assay (CrAg, IMMY, Norman, OK) is a point of care test (POCT) with sensitivity close to 100% and 95% specificity. WHO has recommended CrAg screening in patients with advanced HIV disease. It is used worldwide due to its...
3D-Printed Portable Robotic Mobile Microscope for Remote Diagnosis of Global Health Diseases
Microscopy plays a crucial role in the diagnosis of numerous diseases. However, the need for trained microscopists and pathologists, the complexity of pathology, and the accessibility and affordability of the technology can hinder the provision of rapid and...
Mobile microscopy and telemedicine platform assisted by deep learning for quantification of Trichuris trichiura infection
Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). Kato-Katz technique is the diagnosis method recommended by WHO and although is generally more sensitive than other microscopic methods in high...
Red de laboratorios de Chagas: Ejercicio virtual de intercomparación de imágenes microscópicas digitalizadas
Introducción/Objetivos En España, la enfermedad de Chagas (EC) es una infección parasitaria predominantemente importada, cuya principal vía de transmisión es la vertical de madre a hijo durante el embarazo o el parto. La detección temprana de esta infección permite...
Stitching Methodology for Whole Slide Low-Cost Robotic Microscope Based on a Smartphone
This work is framed within the general objective of helping to reduce the cost of telepathology in developing countries and rural areas with no access to automated whole slide imaging (WSI) scanners. We present an automated software pipeline to the problem of...
Estudio de la funcionalidad de un sistema de telemicroscopía digital para evaluación de la leishmaniasis cutánea
Introducción La leishmaniasis cutánea (LC) es un problema de salud pública y la mayoría de casos ocurren en zonas rurales dispersas. Las nuevas políticas de Salud en línea definidas por la Organización Mundial de la Salud (OMS) con el uso de, mHealth y telemedicina...
Desarrollo e implementación de algoritmo de Inteligencia Artificial basado para la detección de parásitos de malaria
Introducción El diagnóstico de la malaria requiere la confirmación mediante microscopía óptica o test diagnóstico rápido (TDR) de la presencia de parásitos en un paciente enfermo. La microscopía es una técnica fiable que requiere personal formado adecuadamente. La...
Collaborative intelligence and gamification for on-line malaria species differentiation
Background Current World Health Organization recommendations for the management of malaria include the need for a parasitological confirmation prior to triggering appropriate treatment. The use of rapid diagnostic tests (RDTs) for malaria has contributed to a better...
Gamers join real-life fight against malaria and tuberculosis
Despite major progress in the last 15 years, the reduction of the burden of malaria and tuberculosis remains a key objective for global health. Between 2000 and 2014, 43 million lives were saved through effective diagnosis and treatment, but the new UN Sustainable...
Crowdsourcing Malaria Parasite Quantification: An Online Game for Analyzing Images of Infected Thick Blood Smears
Background There are 600,000 new malaria cases daily worldwide. The gold standard for estimating the parasite burden and the corresponding severity of the disease consists in manually counting the number of parasites in blood smears through a microscope, a process...
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