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This project aims to analyze the prediction capability of Optical Coherence Tomography Angiography (OCTA) images for Diabetes Mellitus (DM) and Diabetic Retinopathy (DR,) in a large high-quality image dataset from previous research projects carried out in the field of Ophthalmology (Fundacio¿ La Marato¿ TV3, Fondo Investigaciones Sanitarias, FIS). OCTA is a newly developed, non-invasive, retinal imaging technique that permits adequate delineation of the perifoveal vascular network. It allows the detection of paramacular areas of capillary non perfusion and/or enlargement of the foveal avascular zone (FAZ), representing an excellent tool for assessment of DR.
Apply diffusion-based image generative models to convert videos into a cartoon style (e.g. from a sample image or a descriptive text). Depending on the obtained results a dictionary of styles may be created.
The student will have to implement different learning algorithms of Restricted Boltzmann Machine (RBM) neural networks using CUDA, and compare the performance against a standard CPU implementation.
Study and development of a Reinforcement Learning system for the automatization of dwelling plan generation in the architecture domain
Sovint la salut mental de la mare no es contempla per a la planificació del part, només es treballa la diagnosi i el tractament. Seria possible enfocar-se en la prevenció? Es vol trobar si existeix relació de causalitat entre alguns procediments mèdics com la inducció al part, el part instrumentat o la cesària, i la depressió postpart. Conèixer el percentatge d'embarassos considerats mèdicament de risc i analitzar-ne les veritables amenaces. Establir fins a quin punt aquest risc justifica l'anul·lació de la voluntat de la mare, tenint en compte la seva salut mental.
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