Miguel Luengo-Oroz

Computer Science · Physical Sciences

22h-index2.4kcitations113works7.52yr avg
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Research Topics

Digital Imaging for Blood Diseases(21), Cell Image Analysis Techniques(20), COVID-19 epidemiological studies(15), COVID-19 diagnosis using AI(14), Advanced Fluorescence Microscopy Techniques(11)

Publications113 total

NTDscope: A multi-contrast portable microscope for disease diagnosis
PLOS Global Public Health·2026Open Access
Edge-tuning of artificial intelligence improves diagnostic performance for <i>Schistosomiasis haematobium</i> in a rural setting of Côte d’Ivoire
2025· 2 citedOpen Access
378 | EXPLORING A NEW PROGNOSTIC INDEX IN 341 POST‐TRANSPLANT LYMPHOPROLIFERATIVE DISORDERS IN THE “RITUXIMAB ERA”: A RETROSPECTIVE STUDY FROM SPANISH LYMPHOMA GROUP GELTAMO
Hematological Oncology·2025Open Access
NTDscope: A multi-contrast portable microscope for disease diagnosis
2025· 2 citedOpen Access
Integrating artificial intelligence in drug discovery and early drug development: a transformative approach
Biomarker Research·2025· 85 citedOpen Access
Artificial Intelligence algorithm for real-time detection and counting of <i>Trypanosoma cruzi</i> parasites using smartphone microscopy
2025· 1 citedOpen Access
Enhancing Soil-Transmitted Helminths Diagnosis Through AI: A Self-supervised Learning Approach with Smartphone-Based Digital Microscopy
Communications in computer and information science·2025
Artificial Intelligence Models for Risk Stratification and Prognosis in AML-NOS
Blood·2024· 2 citedOpen Access
Leveraging AI for Predicting Genetic Alterations in Multiple Myeloma through Morphological Analysis of Bone Marrow Aspirates
Blood·2024Open Access
Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay
IMA Fungus·2024· 14 citedOpen Access
Predictive modeling of movements of refugees and internally displaced people: towards a computational framework
2024
How many labels do I need? self-supervised learning strategies for multiple blood parasites classification in microscopy images
2024· 2 cited
Edge Artificial Intelligence (AI) for real-time automatic quantification of filariasis in mobile microscopy
PLoS neglected tropical diseases·2024· 13 citedOpen Access
THE OPPORTUNITIES, LIMITATIONS, AND CHALLENGES IN USING MACHINE LEARNING TECHNOLOGIES FOR HUMANITARIAN WORK AND DEVELOPMENT
Advances in Complex Systems·2024· 1 citedOpen Access
How many labels do I need? Self-supervised learning strategies for multiple blood parasites classification in microscopy images
2024Open Access
Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases
Microscopy and Microanalysis·2024· 5 citedOpen Access
A Smartphone App for Real-Time Assessment of Malaria Prophylaxis Adverse Events
Telemedicine Journal and e-Health·2024
Assessment of Artificial Intelligence Language Models and Information Retrieval Strategies for QA in Hematology
Blood·2023· 2 cited
Evaluation of the Performance of a 3D-Printed Smartphone-Based Retinal Imaging Device as a Screening Tool for Retinal Pathology in Mozambique
American Journal of Tropical Medicine and Hygiene·2023· 2 citedOpen Access
Exploring YouTube’s Recommendation System in the Context of COVID-19 Vaccines: Computational and Comparative Analysis of Video Trajectories
Journal of Medical Internet Research·2023· 14 citedOpen Access
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Frequent Co-authors

A. Santos(12), María J. Ledesma‐Carbayo(12), Nadine Peyriéras(9), Louise Duloquin(8), Paul Bourgine(8), Katherine Hoffmann Pham(8), David Bermejo-Peláez(7), Thierry Savy(6), Daniel Cuadrado(6), Emmanuel Faure(5), Carlos Castro‐González(5), Joseph Aylett-Bullock(5), María Postigo(5), Alex Rutherford(4), David Pastor-Escuredo(4), Elena Dacal(4), Lin Lin(4), Elisa Álamo(3), Alexander Vladimirov(3), José Muñóz(3)