Consolidated Research Group
Artificial Intelligence and Bio-Medical Applications
About us
We are the "Artificial Intelligence and Bio-Medical Applications (AIBA)" Consolidated research group at Universitat de Barcelona, Ref. (2021SGR01094) Recognized by Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR), located in Catalonia, Spain.
Latest News
Prof. Petia’s Prestigious Women Researchers Lecture Series
Prestigious Women Researchers Lecture Series: "How Self-supervised learning can leverage Food Fine-grained recognition" talk given by Prof. Petia Radeva
Inaugural Event of ELLIS Unit Barcelona
The Ellis Unit Barcelona was successfully inaugurated on 12th of July, 2024 Friday at the Institut d’Estudis Catalans (IEC), Barcelona.
TFG Thesis of Oscar Blasquez and Adrian Galan
We are proud to announce that our TFG students achieved the highest grade of 10 on their TFG thesis.
Team Members
Research Lines
Deep Learning
Deep learning, a cutting-edge branch of artificial intelligence, empowers machines to learn from vast datasets and make intelligent decisions. By mimicking the structure and function of the human brain through artificial neural networks, deep learning algorithms excel at tasks such as image recognition, speech synthesis, and language translation. In our team, we harness the potential of deep learning to drive innovation and solve complex problems across various domains.
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Deep learning for food computing
Today Deep learning (DL) is revolutionizing many fields of real problems, beating human performance in problems such as object recognition, lip reading, or cancer detection. However, food recognition and segmentation are still underexplored and underexploited. To address them, we develop highly robust DL algorithms employing Transfer learning, Transformers, Uncertainty modeling and Explainability among others.
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Pathophysiology of Nervous System Diseases
Our team is dedicated to unraveling the complex mechanisms underlying neurological disorders, from Alzheimer's disease to Parkinson's disease and beyond. Through cutting-edge research and interdisciplinary collaboration, we're gaining invaluable insights into the molecular, cellular, and physiological changes that contribute to these conditions. Together, we're working towards innovative treatments and therapies to improve the lives of those affected by these disorders.
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Medical Imaging
Our team is committed to harnessing the power of advanced imaging technologies to improve healthcare outcomes. From X-rays and MRI scans to CT scans and ultrasound, medical imaging plays a crucial role in diagnosis, treatment planning, and monitoring of various medical conditions. Through cutting-edge research and innovation, we're pushing the boundaries of what's possible in medical imaging, developing new techniques and algorithms to enhance image quality, reduce radiation exposure, and increase diagnostic accuracy.
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Artificial Intelligence applied to Health
Our team is dedicated to harnessing the power of AI to revolutionize healthcare. From predictive analytics and diagnostic imaging to personalized treatment recommendations and remote patient monitoring, AI holds the potential to transform every aspect of the healthcare ecosystem. Through cutting-edge research and collaboration with healthcare professionals, we aim to develop innovative AI solutions that improve patient outcomes, increase efficiency, and reduce costs.
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Computer Graphics
Our team is passionate about creating visually stunning and immersive experiences through the power of digital imagery. From video games and animation to virtual reality and augmented reality, computer graphics play a vital role in shaping how we interact with digital content. With a focus on innovation and creativity, our team is dedicated to pushing the boundaries of what's possible in computer graphics, developing cutting-edge techniques and technologies to bring ideas to life in breathtaking detail.
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Machine Learning
We're passionate about harnessing the power of data and algorithms to create intelligent systems that can learn and adapt. From predictive analytics and recommendation systems to autonomous vehicles and medical diagnostics, machine learning is revolutionizing industries and driving innovation. With a focus on cutting-edge research and practical applications, our team is dedicated to pushing the boundaries of what's possible with machine learning, developing new algorithms and techniques to solve complex problems and unlock new opportunities.
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Data Science & Bio-Medical Applications
We're passionate about leveraging data-driven approaches to tackle some of the most pressing challenges in healthcare and life sciences. From analyzing genomic data and identifying biomarkers to predicting disease outcomes and optimizing treatment strategies, data science holds immense potential for revolutionizing biomedical research and patient care. With a focus on cutting-edge methodologies and interdisciplinary collaboration, our team is dedicated to pushing the boundaries of what's possible at the intersection of data science and biomedicine.
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Natural Language Processing (NLP)
We're passionate about harnessing the power of language to create intelligent systems that can understand, interpret, and generate human language. From chatbots and virtual assistants to language translation and sentiment analysis, NLP is revolutionizing how we communicate and interact with technology. With a focus on cutting-edge research and practical applications, our team is dedicated to pushing the boundaries of what's possible with NLP, developing new algorithms and techniques to solve complex language-related problems and unlock new opportunities.
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Statistical and Probabilistic Modeling
Our team is more passionate about harnessing the power of data and probability theory to gain insights, make predictions, and drive decision-making in various fields. From predicting financial trends and analyzing market behavior to modeling complex systems in engineering and science, statistical and probabilistic modeling plays a crucial role in understanding uncertainty and variability. With a focus on cutting-edge methodologies and practical applications, our team is dedicated to pushing the boundaries of what's possible with statistical and probabilistic modeling, developing innovative solutions to solve complex problems and unlock new opportunities.
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Uncertainty Modeling
We're passionate about understanding and quantifying uncertainty in various systems and processes. From predicting the reliability of engineering structures to assessing risk in financial markets and forecasting the impact of climate change, uncertainty modeling and quantification are essential for making informed decisions in the face of uncertainty. With a focus on cutting-edge methodologies and practical applications, our team is dedicated to pushing the boundaries of what's possible in uncertainty modeling and quantification, developing innovative solutions to address complex challenges and mitigate risks.
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Bio-Mechanics
We're dedicated to understanding the mechanical principles underlying biological systems, from the movement of cells and tissues to the biomechanics of human movement and injury prevention. With a focus on interdisciplinary research and practical applications, our team is committed to pushing the boundaries of what's possible in biomechanics, developing innovative solutions to address challenges in healthcare, sports performance, and rehabilitation.
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Bio-Informatics
We're dedicated to leveraging computational tools and techniques to analyze biological data, unlocking new insights and driving discoveries in the life sciences. From studying DNA sequences and protein structures to understanding complex biological pathways and disease mechanisms, bioinformatics plays a crucial role in advancing our understanding of living organisms and their interactions. With a focus on cutting-edge research and practical applications, our team is committed to pushing the boundaries of what's possible in bioinformatics, developing innovative solutions to address key challenges in healthcare, agriculture, and environmental science.
More about this lineLatest publications
Robust Deep Neural Network for Learning in Noisy Multi-Label Food Images
2024 | Roberto Morales, Angela Martinez-Arroyo, Eduardo Aguilar | Sensors 24 (7), 2034, 2024
ChatGPT y educación universitaria: posibilidades y límites de ChatGPT como herramienta docente
2024 | Mireia Ribera, Oliver Díaz | Universitat de Barcelona. IDP/ICE & Ediciones Octaedro, 2024
Joint AAPM Task Group 282/EFOMP Working Group Report: Breast dosimetry for standard and contrast‐enhanced mammography and breast tomosynthesis
2024 | Ioannis Sechopoulos, David R Dance, John M Boone, Hilde T Bosmans, Marco Caballo, Oliver Diaz, Ruben van Engen, Christian Fedon, Stephen J Glick, Andrew M Hernandez, Melissa L Hill, Katie W Hulme, Renata Longo, Carolina Rabin, Wendelien BG Sanderink, J Anthony Seibert | Medical physics 51 (2), 712-739, 2024
Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models
2024 | Richard Osuala, Daniel Lang, Preeti Verma, Smriti Joshi, Apostolia Tsirikoglou, Grzegorz Skorupko, Kaisar Kushibar, Lidia Garrucho, Walter HL Pinaya, Oliver Diaz, Julia Schnabel, Karim Lekadir | arXiv preprint arXiv:2403.13890, 2024
ChatGPT y educación universitaria: posibilidades y límites de ChatGPT como herramienta docente [vídeo]
2024 | Daniel Ortiz Martínez, Eloi Puertas i Prats, Mireia Ribera, Oliver Díaz, Cristina Galván Fernández, Raúl Arango Pérez, Miguel Huayllas Choque, Meritxell Martínez Riera, Roger Angela i Gambús, Jordi Tremosa Armengol | Universitat de Barcelona. Institut de Desenvolupament Professional (IDP-ICE), 2024
Effects of Pre-and Postnatal Early-Life Stress on Internalizing, Adiposity, and Their Comorbidity
2024 | Serena Defina, Tom Woofenden, Vilte Baltramonaityte, Carmine M Pariante, Karim Lekadir, Vincent WV Jaddoe, Fadila Serdarevic, Henning Tiemeier, Esther Walton, Janine F Felix, Charlotte AM Cecil, EarlyCause Consortium | Journal of the American Academy of Child & Adolescent Psychiatry 63 (2), 255-265, 2024
Cohort Profile: The Cardiovascular Research Data Catalogue
2024 | Jaakko Reinikainen, Tarja Palosaari, Alejandro J Canosa-Valls, Carsten O Schmidt, Rita Wissa, Sucharitha Chadalavada, Laia Codó, Josep Lluís Gelpí, Bijoy Joseph, Aad van der Lugt, Elsa Pacella, Steffen E Petersen, Esmeralda Ruiz Pujadas, Liliana Szabo, Tanja Zeller, Teemu Niiranen, Karim Lekadir, Kari Kuulasmaa | International Journal of Epidemiology 53 (1), dyad175, 2024
A structural heart-brain axis mediates the association between cardiovascular risk and cognitive function
2024 | Akshay Jaggi, Eleanor LS Conole, Zahra Raisi-Estabragh, Polyxeni Gkontra, Celeste McCracken, Liliana Szabo, Stefan Neubauer, Steffen E Petersen, Simon R Cox, Karim Lekadir | Imaging Neuroscience 2, 1-18, 2024
Aligning Cancer Research Priorities in Europe with Recommendations for Conquering Cancer: A Comprehensive Analysis
2024 | Denis Horgan, Marc Van den Bulcke, Umberto Malapelle, Nicola Normanno, Ettore D Capoluongo, Arsela Prelaj, Carmelo Rizzari, Aliki Stathopoulou, Jaya Singh, Marta Kozaric, France Dube, Manuel Ottaviano, Stefania Boccia, Gabriella Pravettoni, Ivana Cattaneo, Núria Malats, Reinhard Buettner, Karim Lekadir, Francesco de Lorenzo, Patricia Blanc, Catherine Alix-Panabieres, Sara Badreh, Paul Hofman, Eric Solary, Ruggero De Maria | Healthcare 12 (2), 259, 2024
Tackling the implementation gap for the uptake of NGS and advanced molecular diagnostics into healthcare systems
2024 | Denis Horgan, Marc Van den Bulcke, Umberto Malapelle, Giancarlo Troncone, Nicola Normanno, Ettore D Capoluongo, Arsela Prelaj, Carmelo Rizzari, Dario Trapani, Jaya Singh, Marta Kozaric, John Longshore, Manuel Ottaviano, Stefania Boccia, Gabriella Pravettoni, Ivana Cattaneo, Núria Malats, Reinhard Buettner, Karim Lekadir, Francesco de Lorenzo, Paul Hofman, Ruggero De Maria | Heliyon 10 (1), 2024
New implementation of data standards for AI research in precision oncology. Experience from EuCanImage.
2024 | Teresa Garcia-Lezana, Maciej Bobowicz, Santiago Frid, Michael Rutherford, Mikel Recuero, Katrine Riklund, Aldar Cabrelles, Marlena Rygusik, Lauren Fromont, Roberto Francischello, Emanuele Neri, Salvador Capella, Fred Prior, Jonathan Bona, Pilar Nicolas, Martijn PA Starmans, Karim Lekadir, Jordi Rambla, EuCanImage | medRxiv, 2024.03. 15.24303032, 2024
Bayesian DivideMix++ for Enhanced Learning with Noisy Labels
2024 | Bhalaji Nagarajan, Ricardo Marques, Eduardo Aguilar, Petia Radeva | Neural Networks 172, 106122, 2024
A bootstrap method based on linear regression to estimate COVID-19 Ecological Risk in Catalonia
2023 | Nicolas Ayala-Aldana, Antonio Monleon-Getino, Jaume Canela-Soler, Petia Radeva, Javier Rodenas
DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery
2023 | Jordi Abante, Peter L Wang, Julia Salzman | Genome Biology 24 (1), 240, 2023
DNA methylation entropy is associated with DNA sequence features and developmental epigenetic divergence
2023 | Yuqi Fang, Zhicheng Ji, Weiqiang Zhou, Jordi Abante, Michael A Koldobskiy, Hongkai Ji, Andrew P Feinberg | Nucleic Acids Research, 2023
Assessing Tree-Based Phenotype Prediction on the UK Biobank
2023 | Alex Meléndez, Cayetana López, David Bonet, Gerard Sant, Daniel Mas Montserrat, Jordi Abante, Manuel Rivas, Ferran Marqués, Alexander G Ioannidis | 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2023
Author Correction: The impact of rare germline variants on human somatic mutation processes
2023 | Mischan Vali-Pour, Solip Park, Jose Espinosa-Carrasco, Daniel Ortiz-Martínez, Ben Lehner, Fran Supek | nature communications 14 (1), 5448, 2023
Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging
2023 | Richard Osuala, Kaisar Kushibar, Lidia Garrucho, Akis Linardos, Zuzanna Szafranowska, Stefan Klein, Ben Glocker, Oliver Diaz, Karim Lekadir | Medical Image Analysis 84, 102704, 2023
medigan: a Python library of pretrained generative models for medical image synthesis
2023 | Richard Osuala, Grzegorz Skorupko, Noussair Lazrak, Lidia Garrucho, Eloy García, Smriti Joshi, Socayna Jouide, Michael Rutherford, Fred Prior, Kaisar Kushibar, Oliver Díaz, Karim Lekadir | Journal of Medical Imaging 10 (6), 061403-061403, 2023
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
2023 | Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard O Botwe, Bishesh Khanal, Brigit Beger, Carol C Wu, Celia Cintas, Curtis P Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A González, Folkert W Asselbergs, Fred Prior, Gabriel P Krestin, Gary Collins, Geletaw S Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C Woodruf, Hugo JWL Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W Gichoya, Julia A Schnabel, Kaisar Kushibar, Katrine Riklund, Kensaku Mori, Kostas Marias, Lameck M Amugongo, Lauren A Fromont, Lena Maier-Hein, Leonor Cerdá Alberich, Leticia Rittner, Lighton Phiri, Linda Marrakchi-Kacem, Lluís Donoso-Bach, Luis Martí-Bonmatí, M Jorge Cardoso, Maciej Bobowicz, Mahsa Shabani, Manolis Tsiknakis, Maria A Zuluaga, Maria Bielikova, Marie-Christine Fritzsche, Marius George Linguraru, Markus Wenzel, Marleen De Bruijne, Martin G Tolsgaard, Marzyeh Ghassemi, Md Ashrafuzzaman, Melanie Goisauf, Mohammad Yaqub, Mohammed Ammar, Mónica Cano Abadía, Mukhtar ME Mahmoud, Mustafa Elattar, Nicola Rieke, Nikolaos Papanikolaou, Noussair Lazrak, Oliver Díaz, Olivier Salvado, Oriol Pujol, Ousmane Sall, Pamela Guevara, Peter Gordebeke, Philippe Lambin, Pieta Brown, Purang Abolmaesumi, Qi Dou, Qinghua Lu, Richard Osuala, Rose Nakasi, S Kevin Zhou, Sandy Napel, Sara Colantonio, Shadi Albarqouni, Smriti Joshi, Stacy Carter, Stefan Klein, Steffen E Petersen, Susanna Aussó, Suyash Awate, Tammy Riklin Raviv, Tessa Cook, Tinashe EM Mutsvangwa, Wendy A Rogers, Wiro J Niessen, Xènia Puig-Bosch, Yi Zeng, Yunusa G Mohammed, Yves Saint James Aquino, Zohaib Salahuddin, Martijn Starmans | arXiv preprint arXiv:2309.12325, 2023
