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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
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Posts
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Blog Post number 1
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notwork
ALLEO
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Multidisciplinar work (photography, dance, music and plastic arts, among others) studying movement as an external element of the body.
portfolio
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publications
Identification of Predictive Models Including Polymorphisms in Cytokines Genes Associated with Post-Transplant Complications after Identical HLA-Allogeneic Stem Cell Transplantation
Published in 64th Annual Meeting and Exposition of the American Society of Hematology, Blood, 2022
Recommended citation: Paula Muñiz Sevilla, María Martínez-García, Mi Kwon, Rebeca Bailén, Gillen Oarbeascoa, Diego Carbonell, Julia Suárez González, María Chicano Lavilla, Cristina Andres, Juan Carlos Triviño, Javier Anguita, José Luis Díez-Martín, Pablo Martínez Olmos, Carolina Martinez-Laperche, Ismael Buño; Identification of Predictive Models Including Polymorphisms in Cytokines Genes Associated with Post-Transplant Complications after Identical HLA-Allogeneic Stem Cell Transplantation. Blood 2022; 140 (Supplement 1): 4795–4796. doi: https://doi.org/10.1182/blood-2022-168461 https://ashpublications.org/blood/article/140/Supplement%201/4795/490797/Identification-of-Predictive-Models-Including
Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data
Published in Machine Learning for Health (ML4H) Symposium 2022, 2022
Recommended citation: Moreno-Pino, F., Martínez-García, M., Olmos, P. M., & Artés-Rodríguez, A. (2022). Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data. arXiv preprint arXiv:2211.10371. https://arxiv.org/abs/2211.10371
Sleep Activity Recognition and Characterization from Multi-Source Passively Sensed Data
Published in arXiv (PREPRINT currently under review), 2023
Recommended citation: María Martínez-García, Fernando Moreno-Pino, Pablo M. Olmos, and Antonio Artés-Rodríguez. Sleep activity recognition and characterization from multi-source passively sensed data. arXiv preprint arXiv:2301.10156. https://arxiv.org/abs/2301.10156
Identification of Biomarkers and Risk Factors for Inmune Effector Cell-Associated Neurotoxicity Syndrome (ICANS) in CD19-directed CAR T-Cell Therapy: a Retrospective Machine Learning-based Analysis
Published in EHA 2023 Hybrid Congress, 2023
Recommended citation: M. Gómez-Llobell; M. Martínez-García; C. Serra-Smith; D. Gómez-Costas; G. Oarbeascoa; D.Carbonell; J. Anguita; A. Pérez-Corral; M. Pion; VA Pérez-Fernández; I. García- Fernández; M.Bastos; P. Fernández-Caldas; I. Gómez-Centurión; A. Alarcón; E. Catalá; D. Conde; J. Gayoso; P.Olmos; C. Martínez-Laperche; J. García-Domínguez; Y. Fernández; R. Bailén; M. Kwon; IIdentification of Biomarkers and Risk Factors for Inmune Effector Cell-Associated Neurotoxicity Syndrome (ICANS) in CD19-directed CAR T-Cell Therapy: a Retrospective Machine Learning-based Analysis. EHA2023.
Handling ill-conditioned omics data with deep probabilistic models
Published in IEEE Journal of Biomedical and Health Informatics (Early Access), 2023
Recommended citation: M. Martínez-García and P. M. Olmos, "Handling Ill-conditioned Omics Data with Deep Probabilistic Models," in IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2023.3279493. https://ieeexplore.ieee.org/document/10132455
talks
Handling ill-conditioned omics data with deep probabilistic models.
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Presented the DBLR (Deep Bayesian Logistic Regression) model at the 9ª Jornada de Investigación e Innovación IiSGM.
Handling ill-conditioned omics data with deep probabilistic models.
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Presented the DBLR (Deep Bayesian Logistic Regression) model at the Cambridge ELLIS Machine Learning Summer School 2022.
Application of Probabilistic Machine Learning models in clinical research. Case studies carried by our research group.
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Introduction to Probabilistic Machine Learning and presentation of the last results achieved by our research groups (Grupo de Genética y Clínica de las Neoplasias Hematológicas y el Trasplante Hematopoyético and Grupo de Teoría de la Señal).
teaching
Teacher Assistant in Natural Language Processing
Course, Fundación BBVA, 2022
Teacher Assistant in Neural Networks
Master Course, Universidad Carlos III de Madrid, MASTER IN APPLIED ARTIFICIAL INTELLIGENCE, 2022
The fundamental objective is that the student learns to design decision machines based on neural networks for basic learning problems in tabular and multimedia data, paying special attention to regularization and validation techniques. Likewise, the student will learn to use automatic differentiation software packages for model training and experimental simulation.
Teacher Assistant in Deep Learning
Master Course, Universidad Carlos III de Madrid, MASTER IN APPLIED ARTIFICIAL INTELLIGENCE, 2022
The fundamental objective of this subject is for the student to know and learn to use learning schemes based on advanced neural networks, with special emphasis on computer vision applications, treatment of temporal signals and text, and the adjustment of probabilistic models for the generation of artificial data.
Teacher Assistant in AI in Health
Master Course, Universidad Carlos III de Madrid, MASTER IN APPLIED ARTIFICIAL INTELLIGENCE, 2023
The objectives of the matter are to present the possibilities and limitations of the application of AI in the field of health, to present problems in the field of health in which AI techniques can be applied and develop the capacity to apply AI techniques in some health problems.
Master Thesis Co-director. ‘Unsupervised Genetic Study of Post-Transplant Complications after Identical HLA-Allogeneic Stem Cell Transplantation’
Master Thesis, Universidad Carlos III de Madrid, MASTER IN APPLIED ARTIFICIAL INTELLIGENCE, 2023
Master Thesis Co-director. ‘Deep Survival Analysis in AML patients’
Master Thesis, Universidad Carlos III de Madrid, MASTER IN APPLIED ARTIFICIAL INTELLIGENCE, 2023