• An ECG and echocardiography-based characterization of hypertrophic cardiomyopathy using machine learning

  Leal Bajo, Carla (2023-09-22)

  Hypertrophic cardiomyopathy (HCM) is a condition characterized by an abnormal thickening of the myocardium resulting in impaired blood pumping efficiency of the heart. HCM exhibits clinical variability, with diverse ...
• On the basis of impaired functional connectivity in psychosis: the role of structural substrate and neurometabolites contribution

  González Aranceta, Nerea (2023-09-22)

  Psychotic disorders are characterized by the presence of symptoms related to a distortion of one’s perception of reality. In its early stages (First Episode of Psychosis, FEP), patients may show diffuse symptomatology ...
• The use of whole-brain models and variational autoencoders for the low-dimensional representation of psychosis and its perturbational landscape

  Garcés de Marcilla Lappin, Iraïs (2023-09-22)

  Psychosis can be described as an alteration in brain connectivity that leads to an impairment of cognition and the speed at which the information gets processed, what causes a diversity of psychiatric symptoms. This ...
• Automatic segmentation of intramedullary multiple sclerosis lesions delimited in DIR sequences with convolutional neural networks

  Gambús i Moreno, Paula (2023-09-22)

  Multiple sclerosis (MS) is a neurodegenerative disease affecting the central nervous system (CNS), characterized by the destruction of myelin sheaths, that has become the leading cause of disability in young adults. Since ...
• Design and development of a mockup of the circulation to test wireless implantable pressure sensors powered and controlled by volume conduction

  Gadea Saez, Mar (2023-09-22)

  Arterial blood pressure is a crucial indicator for cardiac conditions like hypertension, heart failure, strokes and limb ischemia. Current wireless devices diagnose heart failure through blood pressure measurement. ...
• Automatic aetiology identification of left ventricular hypertrophy from magnetic resonance cine sequences

  Clua i Sánchez, Estel (2023-09-22)

  Left ventricular hypertrophy (LVH) consists of the thickening of the myocardium, significantly increasing the risk of cardiovascular events. LVH can be attributed to various etiologies, each with distinct prognoses and ...
• Simulating the influence of proteoglicans changes in intervertebral disc mechanical behaviour

  Blanco Villaverde, Inés (2023-09-22)

  Around 80% of world population will suffer of low back pain (LBP). Such condition is often related with intervertebral disc (IVD) degeneration (DD). In DD, the proteoglycan (PG) loss is highly important since it compromises ...
• Device-related thrombus in transcatheter aortic valve implantation: a fluid-structure interaction study

  Barrouhou Berrouhou, Manal (2023-09-22)

  Transcatheter aortic valve implantation (TAVI) is a minimally invasive heart procedure that has emerged as a safe and effective treatment for patients with severe symptomatic aortic stenosis (AS). This is a common heart ...
• Quantification and analysis of atrial focal activity in atrial fibrillation using electrocardiographic imaging and flattening algorithms

  Fisa i Millan, Maria (2023-09-22)

  Atrial fibrillation (AF) is a prevalent cardiac arrhythmia, yet understanding its causes and finding effective treatments remains a challenge. To address this, researchers are developing innovative approaches based on ...
• Personalization of epileptogenic network models based on connectivity analysis

  Félez Martínez, Esteban (2023-09-22)

  The use of computational brain models in epilepsy constitutes a powerful tool not only to improve our understanding of the disease, but also to optimize and personalize treatments in silico. In this direction, properly ...
• Impact of alveolar bone grafting on bone resorption in patients with cleft lip and palate: a 3D analysis

  Engli Rueda, Martí (2023-09-22)

  A cleft lip and palate are congenital defects that occur when the tissues of the face and mouth do not fuse properly during fetal development. These defects often require the use of bone grafts to achieve successful ...
• In-silico models of arteriovenous fistulas in patients with end-stage renal disease

  Martínez Dalmau, Lídia (2023-09-22)

  End-stage renal disease (ESRD) is a life-threatening condition that affects over 10% of the global population, necessitating hemodialysis (HD) for patients awaiting a kidney transplant. The arteriovenous fistula (AVF) ...
• Inverse optimal control for modeling virus mutations in SARS-CoV-2

  Meijer, Ilse (2022)

  Inverse Optimal Control (IOC) deals with the problem of recovering an unknown cost function in a Markov decision process from expert demonstrations acting optimally. In this thesis we apply IOC to SARS-CoV-2 data. For ...
• Extraction and categorization of Japanese lexical collocations with graph-aware transformers

  Nisho, Kosuke James (2022)

  Lexical collocations may be identified and categorized in context, which is helpful for language acquisition, dictionary creation, and many other downstream NLP tasks. However, the automatic collocation extraction and ...
• Taxonomic classification of metagenomic reads using machine learning models

  Alcobé Garcia, Eduard (2022)

  Microorganisms such as bacteria can be hard to identify correctly. Most current classification techniques are based on well conserved genes, for instance the 16S ribosomal RNA (16S rRNA). Nevertheless, achieving a ...
• Task and motion planning: scaling up

  Dalmau Moreno, Magí (2022)

  This master thesis contributes to provide planning capabilities to embodied agents so that they are able to decide what sequence of actions should be taken to solve a given complex problem, involving coupled reasoning ...
• A novel message passing approach to spatial air quality prediction in urban areas

  Calo Oliveira, Sergio (2022)

  Air pollution in our cities is a very significant cause of death and worsening of the quality of life in current times. Knowing in depth this phenomenon and its details and building tools that help us to mitigate its ...
• Linguistic emergence in deep neural networks

  Locatelli Metz, Davide (2022)

  Recent work in Emergent Communication has shown that deep neural networks can develop successful strategies of referential communication. Arguably, the extent to which they can do so depends on the properties of the ...
• Exploration of articular cartilage biomechanical response during gait of patient with knee osteoarthritis using finite element models

  Giménez Lozano, Marina (2022)

  Knee osteoarthritis (OA) is one of the most prevalent forms of arthritis and one of the leading causes of disability. The pathological traits consist of articular cartilage degradation and bone thickening, among other ...
• Aplicación de técnicas computacionales de extracción y análisis de datos para entender mejor la ciendia ciudadana

  Martínez Almansa, Mara (2022)

  La ciencia ciudadana es un nuevo proceso participativo que se utiliza en ciencia que permite a cualquier ciudadano participar en proyectos científicos. CS Track es un proyecto Europeo H2020 que tiene como objetivo ampliar ...

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