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Miguel Angel Luengo-Oroz

Miguel Angel Luengo-Oroz

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124
Publications
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Publications

Publications (124)
Article
Full-text available
The coordination of humanitarian relief, e.g. in a natural disaster or a conflict situation, is often complicated by a scarcity of data to inform planning. Remote sensing imagery, from satellites or drones, can give important insights into conditions on the ground, including in areas which are difficult to access. Applications include situation awa...
Preprint
Full-text available
Solidarity is one of the fundamental values at the heart of the construction of peaceful societies and present in more than one third of world's constitutions. Still, solidarity is almost never included as a principle in ethical guidelines for the development of AI. Solidarity as an AI principle (1) shares the prosperity created by AI, implementing...
Article
Full-text available
In an unprecedented effort of scientific collaboration, researchers across fields are racing to support the response to COVID-19. Making a global impact with AI tools will require scalable approaches for data, model and code sharing; adapting applications to local contexts; and cooperation across borders.
Article
Full-text available
Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). The Kato-Katz technique is the diagnosis method recommended by the World Health Organization (WHO) although it often presents a decreased sensitivity in low transmission settings and it is labour intensive. Visual reading of Kato...
Article
Full-text available
The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts...
Article
The diagnosis of multiple myeloma (MM) heavily relies on the cytomorphological analysis of bone marrow aspirate (BMA), supplemented by cytometry and genetic analysis of cytogenetic alterations, which hold critical prognostic and therapeutic implications. Key genetic alterations such as translocation t(11;14),gain 1q (+1q), deletion (del) 17p, and d...
Article
Introduction Despite recent therapeutic advances in acute myeloid leukemia (AML), the prognosis remains unfavorable, with mortality rates ranging from 50-80%. The current prognostic classification by the European Leukemia Net (ELN 2022) stratifies patients into favorable, intermediate, and adverse risk categories based on recurrent genetic abnormal...
Article
Full-text available
Objectives Cryptococcosis remains a severe global health concern, underscoring the urgent need for rapid and reliable diagnostic solutions. Point-of-care tests (POCTs), such as the cryptococcal antigen semi-quantitative (CrAgSQ) lateral flow assay (LFA), offer promise in addressing this challenge. However, their subjective interpretation poses a li...
Article
Full-text available
Filariasis, a neglected tropical disease caused by roundworms, is a significant public health concern in many tropical countries. Microscopic examination of blood samples can detect and differentiate parasite species, but it is time consuming and requires expert microscopists, a resource that is not always available. In this context, artificial int...
Article
Novel digital data sources and tools like machine learning (ML) and artificial intelligence (AI) have the potential to revolutionize data about development and can contribute to monitoring and mitigating humanitarian problems. The potential of applying novel technologies to solving some of humanity’s most pressing issues has garnered interest outsi...
Preprint
Full-text available
A bstract Bloodborne parasitic diseases such as malaria, filariasis or chagas pose significant challenges in clinical diagnosis, with microscopy as the primary tool for diagnosis. However, limitations such as time-consuming processes and the dependence on trained microscopists is critical, particularly in resource-constrained settings. Deep learnin...
Article
Analysis of bone marrow aspirates (BMAs) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on a visual examination of samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability. In this wor...
Article
Background: Growth of international travel to malarial areas over the last decades has contributed to more travelers taking malaria prophylaxis. Travel-related symptoms may be wrongly attributed to malaria prophylaxis and hinder compliance. Here, we aimed to assess the frequency of real-time reporting of symptoms by travelers following malaria prop...
Article
Introduction Large language models (LLMs) have gained popularity due to their natural language generation and interpretation capabilities. Integrating these models in medicine enables multiple tasks like summarizing medical histories, synthesizing literature, and suggesting diagnoses. Models like ChatGPT, GPT-4, and Med-PaLM2 (Singhal et al., 2023)...
Article
Low-income countries carry approximately 90% of the global burden of visual impairment, and up to 80% of this could be prevented or cured. However, there are only a few studies on the prevalence of retinal disease in these countries. Easier access to retinal information would allow differential diagnosis and promote strategies to improve eye health...
Article
Full-text available
Background Throughout the COVID-19 pandemic, there has been a concern that social media may contribute to vaccine hesitancy due to the wide availability of antivaccine content on social media platforms. YouTube has stated its commitment to removing content that contains misinformation on vaccination. Nevertheless, such claims are difficult to audit...
Preprint
Full-text available
Filariasis, a neglected tropical disease caused by roundworms, is a significant public health concern in many tropical countries. Microscopic examination of blood samples can detect and differentiate parasite species, but it is time consuming and requires expert microscopists, a resource that is not always available. In this context, artificial int...
Preprint
Full-text available
Novel digital data sources and tools like machine learning (ML) and artificial intelligence (AI) have the potential to revolutionize data about development and can contribute to monitoring and mitigating humanitarian problems. The potential of applying novel technologies to solving some of humanity's most pressing issues has garnered interest outsi...
Preprint
BACKGROUND Throughout the COVID-19 pandemic, there has been a concern that social media may contribute to vaccine hesitancy due to the wide availability of antivaccine content on social media platforms. YouTube has stated its commitment to removing content that contains misinformation on vaccination. Nevertheless, such claims are difficult to audit...
Preprint
Humanitarian agencies must be prepared to mobilize quickly in response to complex emergencies, and their effectiveness depends on their ability to identify, anticipate, and prepare for future needs. These are typically highly uncertain situations in which predictive modeling tools can be useful but challenging to build. To better understand the nee...
Article
Full-text available
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 of use. The cryptococcal antigen (CrAg) lateral flow assay (LFA) has demonstrated...
Preprint
Full-text available
Analysis of bone marrow aspirates (BMA) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on visual examination of the samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability. In this wo...
Preprint
AI is being increasingly used to aid response efforts to humanitarian emergencies at multiple levels of decision-making. Such AI systems are generally considered as stand-alone for decision support, with ethical assessments, guidelines and frameworks applied to them through this lens. However, as the prevalence of AI increases in this domain, such...
Article
Predicting forced displacement is an important undertaking of many humanitarian aid agencies, which must anticipate flows in advance in order to provide vulnerable refugees and Internally Displaced Persons (IDPs) with shelter, food, and medical care. While there is a growing interest in using machine learning to better anticipate future arrivals, t...
Article
Full-text available
Timely, accurate, and comparative data on human mobility is of paramount importance for epidemic preparedness and response, but generally not available or easily accessible. Mobile phone metadata, typically in the form of Call Detail Records (CDRs), represents a powerful source of information on human movements at an unprecedented scale. In this wo...
Article
Full-text available
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 clinical outcomes, and to compare the prediction performance with respect to human reade...
Article
Full-text available
Worldwide, TB is one of the top 10 causes of death and the leading cause from a single infectious agent. Although the development and roll out of Xpert MTB/RIF has recently become a major breakthrough in the field of TB diagnosis, smear microscopy remains the most widely used method for TB diagnosis, especially in low- and middle-income countries....
Preprint
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 To evaluate an artificial intelligence-based smartphone application, connected to a web telemedicine platform, to automatically and objectively...
Article
Full-text available
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: To evaluate an artificial intelligence-based smartphone application, connected to a cloud web platform, to automatically and objectively re...
Article
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 international travelers. Methods Participants over 18 years old attending our trave...
Preprint
Full-text available
Objectives To evaluate an artificial intelligence-based smartphone application to automatically and objectively read rapid diagnostic test (RDT) results and assess its impact on COVID-19 pandemic management. Methods Overall, 252 human sera from individuals with PCR-positive SARS-CoV-2 infection were used to inoculate a total of 1165 RDTs for train...
Preprint
Predicting forced displacement is an important undertaking of many humanitarian aid agencies, which must anticipate flows in advance in order to provide vulnerable refugees and Internally Displaced Persons (IDPs) with shelter, food, and medical care. While there is a growing interest in using machine learning to better anticipate future arrivals, t...
Conference Paper
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 Diseases. It is diagnosed by manual examination of stool samples by microscopy, which is...
Article
Full-text available
The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations most affected. Given their density and available infrastructure, refugee and internally displaced person (IDP) settlements can be partic...
Article
Full-text available
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 high-quality diagnoses and healthcare. In this work, we present an affordable, 3D-printed, p...
Preprint
Full-text available
Natural language processing (NLP) plays a significant role in tools for the COVID-19 pandemic response, from detecting misinformation on social media to helping to provide accurate clinical information or summarizing scientific research. However, the approaches developed thus far have not benefited all populations, regions or languages equally. We...
Preprint
Full-text available
Timely, accurate, and comparative data on human mobility is of paramount importance for epidemic preparedness and response, but generally not available or easily accessible. Mobile phone metadata, typically in the form of Call Detail Records (CDRs), represents a powerful source of information on human movements at an unprecedented scale. In this wo...
Article
bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">As secretary general of the United Nations, Antonio Guterres said during the 2020 Nelson Mandela Annual Lecture, “COVID-19 has been likened to an X-ray, revealing fractures in the fragile skeleton of the societies we have built.” Without a doubt, the COV...
Preprint
Full-text available
The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world's most vulnerable populations most affected. Given their density and available infrastructure, refugee and internally displaced person (IDP) settlements can be partic...
Article
We invited authors of selected Comments and Perspectives published in Nature Machine Intelligence in the latter half of 2019 and first half of 2020 to describe how their topic has developed, what their thoughts are about the challenges of 2020, and what they look forward to in 2021.
Preprint
Full-text available
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 transmission settings, it often presents a decreased sensitivity in low transmission s...
Chapter
Natural language processing (NLP) plays a significant role in tools for the COVID-19 pandemic response, from detecting misinformation on social media to helping to provide accurate clinical information or summarizing scientific research. However, the approaches developed thus far have not benefited all populations, regions or languages equally. We...
Article
Full-text available
COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of August 5, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID1...
Preprint
Full-text available
The COVID-19 pandemic has been a major challenge to humanity, with 12.7 million confirmed cases as of July 13th, 2020 [1]. In previous work, we described how Artificial Intelligence can be used to tackle the pandemic with applications at the molecular, clinical, and societal scales [2]. In the present follow-up article, we review these three resear...
Article
In addition to moving people and goods, ships can spread disease. Vessel trajectory data from ship Automatic Identification Systems (AIS) is available online and can be extracted and analyzed, as we illustrate in the case of the current coronavirus epidemic. This data should be included in epidemiological models of disease transmission to complemen...
Article
Full-text available
Humanitarian response to natural disasters and conflicts can be assisted by satellite image analysis. In a humanitarian context, very specific satellite image analysis tasks must be done accurately and in a timely manner to provide operational support. We present PulseSatellite, a collaborative satellite image analysis tool which leverages neural n...
Preprint
Full-text available
COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 294,000 cases as of March 22nd 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis at different sca...
Preprint
Full-text available
In addition to moving people and goods, ships can spread disease. Ship traffic may complement air traffic as a source of import risk, and cruise ships - with large passenger volumes and multiple stops - are potential hotspots, in particular for diseases with long incubation periods. Vessel trajectory data from ship Automatic Identification Systems...
Preprint
Full-text available
Humanitarian response to natural disasters and conflicts can be assisted by satellite image analysis. In a humanitarian context, very specific satellite image analysis tasks must be done accurately and in a timely manner to provide operational support. We present PulseSatellite, a collaborative satellite image analysis tool which leverages neural n...
Conference Paper
Full-text available
Human mobility plays a central role in the spatial spread of human infectious diseases. Accurate data on human mobility is therefore key to properly design epidemic models that allow to timely assess the spatial propagation of infectious diseases and to evaluate appropriate control measures and intervention strategies. In this context, mobile phone...
Chapter
In this chapter, we contribute a methodological framework for measuring integration through the lens of spatial and social segregation using CDR data. We illustrate the application of this framework using the datasets provided by Türk Telekom. Integration is one of the main durable solutions to refugee crises recognized by the UN High Commissioner...
Chapter
Call Detail Records have great potential to drive humanitarian action for early warning, monitoring, decision-making, and evaluation. The Data For Development Challenge leveraged mobile phone data for Development in Senegal. We further explored methodologies and protocols to use this data to support humanitarian action for refugees. Obtaining estim...
Preprint
Full-text available
Automated text generation has been applied broadly in many domains such as marketing and robotics, and used to create chatbots, product reviews and write poetry. The ability to synthesize text, however, presents many potential risks, while access to the technology required to build generative models is becoming increasingly easy. This work is align...
Preprint
Full-text available
Social vulnerability is defined as the capacity of individuals and social groups to respond to any external stress placed on their livelihoods and wellbeing. Mobility and migrations are relevant when assessing vulnerability since the movements of a population reflect on their livelihoods, coping strategies and social safety nets. Although in genera...
Article
Full-text available
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 infection recognition and a more targeted treatment. Nevertheless, low-density infe...
Article
Full-text available
The breadcrumbs we leave behind when using our mobile phones—who somebody calls, for how long, and from where—contain unprecedented insights about us and our societies. Researchers have compared the recent availability of large-scale behavioral datasets, such as the ones generated by mobile phones, to the invention of the microscope, giving rise to...
Article
Full-text available
Background Zika virus has created a major epidemic in Central and South America, especially in Brazil, during 2015–16. The infection is strongly associated with fetal malformations, mainly microcephaly, and neurological symptoms in adults. During the preparation of the Rio de Janeiro Olympic Games in 2016, members of Olympic Delegations worldwide e...
Article
Full-text available
Zipf-like distributions characterize a wide set of phenomena in physics, biology, economics and social sciences. In human activities, Zipf-laws describe for example the frequency of words appearance in a text or the purchases types in shopping patterns. In the latter, the uneven distribution of transaction types is bound with the temporal sequences...
Article
Full-text available
Trip Doctor®, a Smartphone-based app monitoring system, was developed to detect infections among travelers in real-time. For testing, 106 participants were recruited (62.2% male, mean age 36 years (SD = 11)). Majority of trips were for tourism and main destinations were in South East Asia. Mean travel duration was 14 days (SD = 10). Diarrhea was th...
Article
Full-text available
We propose a framework for the systematic analysis of mobile phone data to identify relevant mobility profiles in a population. The proposed framework allows finding distinct human mobility profiles based on the digital trace of mobile phone users characterized by a Matrix of Individual Trajectories (IT-Matrix). This matrix gathers a consistent and...
Data
Length of occupation by density of population. Histograms and associated boxplots corresponding to the length of occupation of the population density in each livelihood 1-13 up-down, left-right (see S1 Fig). Blue histograms show the distribution of the raw CDRs in monthly resolution. Red histograms show the distribution of the interpolated data in...
Data
Normalized Difference Vegetation Index. (PDF)
Data
Senegalese segmentation into livelihood zones. Left: Map shows the segmentation of Senegal into different livelihood zones. Right: Summary of each livelihood zone main characteristics (further information in [21]). (EPS)
Data
Senegalese segmentation into arrondissements. The color indicates the livelihood assigned to each arrondissement, which is the one with larger overlapping area with the arrondissement surface. Antenna locations are also displayed with red dots. (EPS)
Data
Completed vs original CDR-based population count at monthly resolution. Dynamic population count for each livelihood (colors match the map in S1 Fig). They were computed by counting the users located within the livelihood shapefile. Right columns show the completed count after daily interpolation and temporal aggregation (Material and methods) and...
Data
Rainfall estimations from NASA-TRMM project. (PDF)
Data
Mobility profiles and livelihood calendars. Alignment of the sylvo-pastoral livelihood (yellow livelihood in S1 Fig) calendar and the derived mobility profiles for the livelihood. (EPS)
Data
Livelihoods and source income calendars. (PDF)