Functional brain perfusion evaluation with Arterial Spin Labeling at 3 Tesla

Dissertation submitted in Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the degree of Master of Biomedical EngineeringBackground: The new clinically available arterial spin labelling (ASL) sequences present some advantages relatively to the commonly used blood oxygenation level dependent (BOLD) method for functional brain studies using magnetic resonance imaging (MRI), namely the fact of being potentially quantitative and more reproducible. Purpose: The main aim of this work was to evaluate the functional use of a commercial ASL sequence implemented on a 3 Tesla MRI system (Siemens, Verio) in the Imaging Department of Hospital da Luz. The first aim was to obtain a functional validation of this technique by comparison with the BOLD contrast, using a number of different approaches. The second aim was to accomplish perfusion quantification, by resolving some important quantification issues. Materials and Methods: Fifteen adult volunteers participated in a single functional imaging session using three different protocols: one using BOLD and two using ASL. The subjects performed a motor finger tapping task and the data analysis was performed using Siemens Neuro3D and FSL (FMRIB’s Software Library). The location and variability of the activated areas were analysed in MNI (Montereal Neurological Institute) standard space. Results: Topographic agreement between the activated regions obtained by BOLD and ASL was found. However, the results show that inter-subject variability and distance to the hand motor cortex were smaller when measured with ASL as compared with BOLD fMRI. Quantitative studies revealed that ASL allows the calculation of cerebral blood flow (CBF), both at baseline and upon functional activation. Conclusion: The results suggest that the functional imaging protocols using ASL produce comparable results to a conventional BOLD protocol, with the additional advantages of reduced inter-subject variability, better spatial specificity and quantification possibilities

Anticipating User Needs: Insights from Design Fiction on Conversational Agents for Computational Thinking

Computational thinking, and by extension, computer programming, is notoriously challenging to learn. Conversational agents and generative artificial intelligence (genAI) have the potential to facilitate this learning process by offering personalized guidance, interactive learning experiences, and code generation. However, current genAI-based chatbots focus on professional developers and may not adequately consider educational needs. Involving educators in conceiving educational tools is critical for ensuring usefulness and usability. We enlisted \numParticipants{} instructors to engage in design fiction sessions in which we elicited abilities such a conversational agent supported by genAI should display. Participants envisioned a conversational agent that guides students stepwise through exercises, tuning its method of guidance with an awareness of the educational background, skills and deficits, and learning preferences. The insights obtained in this paper can guide future implementations of tutoring conversational agents oriented toward teaching computational thinking and computer programming.Comment: 17 pages, three figures, accepted at Conversations 2023 but not yet published in workshop proceeding

Propuesta para el desarrollo de aplicativo para el proceso de ventas en la empresa Calimod

Calimod es una de las compañías más destacadas del país. y se encuentra bien posicionado en el mercado peruano gracias al esfuerzo constante a través de los años y de poner al alcance de sus clientes los diversos productos que se caracterizan por ser de reconocida calidad. Pero ello no le bastará para poder mantenerse en la misma posición en el mercado a través del tiempo ya que las empresas rivales han desarrollado servicios tecnológicos integrados a sus procesos de venta, lo cual los hace mucho más eficientes que Calimod. En este sentido si se desea mantenerse o escalar más peldaños sobre sus competidores en el corto y mediano plazo requerirá hacer mayores esfuerzos para seguir posicionándose y estar sobre el nivel de su competencia. Para ello requerirá transformar sus procesos de venta que actualmente se registran íntegramente de forma manual en fichas de papel, además, a ello se suma que su personal de ventas tiene problemas de disponibilidad de información en línea de los Ítems (Productos) que ofrece a sus clientes, tanto en modelo, cantidad, talla, colores. Esto causa que en la mayoría de las veces se pierdan ventas las cuales se calculan aproximadamente en un 6% de las ventas totales. La presente propuesta busca diseñar un desarrollo móvil que contribuya al proceso de venta y además de proporcionar información sobre los productos existentes. Para ello seentregará una tableta en una primera etapa a un grupo de 20 vendedores con la finalidad que tenga acceso por internet al catálogo de productos e información necesaria para realizar sus ventas, además de disponer de una ficha para el registro de pedidos. Cabe resaltar que la presente propuesta de prototipo es el producto de evaluaciones técnicas que se ha realizado con la colaboración de los usuarios quienes utilizarán el sistema de gestión de ventas.Calimod is one of the most prominent companies in the country. and is well positioned in the Peruvian market thanks to the constant effort over the years and to make available to its customers the various products that are characterized by being of recognized quality. But this will not be enough to keep it in the same position in the market through time since rival companies have developed technological services integrated to their sales processes, which makes them much more efficient than Calimod. In this sense, if you want to keep or climb more steps over your competitors in the short and medium term, you will need to make greater efforts to continue positioning yourself and be above the level of your competition. This will require transforming their sales processes that are currently recorded entirely manually in paper files, in addition, it is added that its sales staff has problems with the availability of online information of the items (products) offered to its customers, both in model, quantity, size, colors. This causes that in most of the times sales are lost which are calculated approximately in a 6% of the total sales. This proposal seeks to design a mobile development that contributes to the sales process and also provides information on existing products. To this end, a tablet will be delivered in a first stage to a group of 20 salespeople with the purpose of providing them with access to the product catalogue and information necessary to make their sales via the Internet, as well as having a file for registering orders.Trabajo de investigaciónCampus Lima Centr

Point process models for novelty detection on spatial point patterns and their extremes

Novelty detection is a particular example of pattern recognition identifying patterns that departure from some model of "normal behaviour". The classification of point patterns is considered that are defined as sets of N observations of a multivariate random variable X and where the value N follows a discrete stochastic distribution. The use of point process models is introduced that allow us to describe the length N as well as the geometrical configuration in data space of such patterns. It is shown that such infinite dimensional study can be translated into a one-dimensional study that is analytically tractable for a multivariate Gaussian distribution. Moreover, for other multivariate distributions, an analytic approximation is obtained, by the use of extreme value theory, to model point patterns that occur in low-density regions as defined by X. The proposed models are demonstrated on synthetic and real-world data sets

Modelling physiological deterioration in post-operative patient vital-sign data

Patients who undergo upper-gastrointestinal surgery have a high incidence of post-operative complications, often requiring admission to the intensive care unit several days after surgery. A dataset comprising observational vital-sign data from 171 post-operative patients taking part in a two-phase clinical trial at the Oxford Cancer Centre, was used to explore the trajectory of patients’ vital-sign changes during their stay in the post-operative ward using both univariate and multivariate analyses. A model of normality based vital-sign data from patients who had a “normal” recovery was constructed using a kernel density estimate, and tested with “abnormal” data from patients who deteriorated sufficiently to be re-admitted to the intensive care unit. The vital-sign distributions from “normal” patients were found to vary over time from admission to the post-operative ward to their discharge home, but no significant changes in their distributions were observed from halfway through their stay on the ward to the time of discharge. The model of normality identified patient deterioration when tested with unseen “abnormal” data, suggesting that such techniques may be used to provide early warning of adverse physiological events

Estimation of respiratory rate from motion contaminated photoplethysmography signals incorporating accelerometry.

Estimation of respiratory rate (RR) from photoplethysmography (PPG) signals has important applications in the healthcare sector, from assisting doctors onwards to monitoring patients in their own homes. The problem is still very challenging, particularly during the motion for large segments of data, where results from different methods often do not agree. The authors aim to propose a new technique which performs motion reduction from PPG signals with the help of simultaneous acceleration signals where the PPG and accelerometer sensors need to be embedded in the same sensor unit. This method also reconstructs motion corrupted PPG signals in the Hilbert domain. An auto-regressive (AR) based technique has been used to estimate the RR from reconstructed PPGs. The proposed method has provided promising results for the estimation of RRs and their variations from PPG signals corrupted with motion artefact. The proposed platform is able to contribute to continuous in-hospital and home-based monitoring of patients using PPG signals under various conditions such as rest and motion states

Mucocutaneous Leishmaniasis with Oral Manifestation: Case Report

La Leishmaniasis es un grupo de enfermedades transmitidas por vectores y causada por la Leishmania, un parásito intracelular, que se presenta de preferencia en regiones tropicales y subtropicales. Se manifiesta mediante un amplio rango de formas clínicas como la cutánea, mucocutánea, y visceral, dependiendo de la especie y respuesta inmunológica del paciente. Se presenta el caso de un hombre de 35 años que acudió derivado a Unidad de Estomatología del Hospital Señor del Milagro, Salta, Argentina, presentando en la cavidad oral lesión, granulomatosa, ulcerada, dolorosa a la palpación, única, en paladar blando, de tres meses de evolución. Se realizaron estudios serológicos, parasitológicos y PCR. Los ELISAs lisados, PCRs y cultivos de materiales de lesiones fueron positivos, confirmando diagnóstico de leishmaniasis mucocutánea. El paciente fue derivado al Servicio de Dermatología donde recibió tratamiento con Antimoniato de Meglumina, con repuesta clínica favorable. El conocimiento de las manifestaciones orales puede llevar al diagnóstico clínico de leishmaniasis mucocutánea por parte del odontólogo, pudiendo entregar un tratamiento oportuno y a la vez ayudar al paciente, evitando complicaciones de esta enfermedad.Leishmaniasis is a group of vector-borne diseases caused by Leishmania, an intracellular parasite, which occurs preferentially in tropical and subtropical regions. It manifests itself through a wide range of clinical forms such as cutaneous, mucocutaneous, and visceral, depending on the species and the patient's immune response. We present a case of a 35-year-old man who was referred to the Stomatology Unit of the Señor del Milagro Hospital, Salta, Argentina, presenting in the oral cavity lesion, granulomatous, ulcerated, painful on palpation, unique, soft palate with three months of evolution. Serological, parasitological and PCR studies were performed. Lysed ELISAs, PCRs and cultures of lesion materials were positive, confirming diagnosis of mucocutaneous leishmaniasis. The patient was referred to the Dermatology Service where he received treatment with Meglumine Antimony, with favorable clinical response. The knowledge of the oral manifestations can lead to the clinical diagnosis of mucocutaneous leishmaniasis by the dentist, being able to provide timely treatment and at the same time help the patient, avoiding complications of this disease.Fil: Molina Avila, Ignacio Javier. Hospital Señor del Milagro; ArgentinaFil: Pimentel Sola, Juan Martin. Hospital Señor del Milagro; ArgentinaFil: Garcia Bustos, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Pimentel Solá, María Julia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Marco, Jorge Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Brunetto, Guadalupe. Hospital Señor del Milagro; ArgentinaFil: Córdoba, Mauree. Hospital Señor del Milagro; ArgentinaFil: Cordero Torres, Karina. Universidad de Viña del Mar (uvm)

A multivariate timeseries modeling approach to severity of illness assessment and forecasting in ICU with sparse, heterogeneous clinical data

The ability to determine patient acuity (or severity of illness) has immediate practical use for clinicians. We evaluate the use of multivariate timeseries modeling with the multi-task Gaussian process (GP) models using noisy, incomplete, sparse, heterogeneous and unevenly-sampled clinical data, including both physiological signals and clinical notes. The learned multi-task GP (MTGP) hyperparameters are then used to assess and forecast patient acuity. Experiments were conducted with two real clinical data sets acquired from ICU patients: firstly, estimating cerebrovascular pressure reactivity, an important indicator of secondary damage for traumatic brain injury patients, by learning the interactions between intracranial pressure and mean arterial blood pressure signals, and secondly, mortality prediction using clinical progress notes. In both cases, MTGPs provided improved results: an MTGP model provided better results than single-task GP models for signal interpolation and forecasting (0.91 vs 0.69 RMSE), and the use of MTGP hyperparameters obtained improved results when used as additional classification features (0.812 vs 0.788 AUC).Intel Science and Technology Center for Big DataNational Institutes of Health. (U.S.). National Library of Medicine (Biomedical Informatics Research Training Grant NIH/NLM 2T15 LM007092-22)National Institute of Biomedical Imaging and Bioengineering (U.S.) (R01 Grant EB001659)Singapore. Agency for Science, Technology and Research (Graduate Scholarship

A multivariate timeseries modeling approach to severity of illness assessment and forecasting in ICU with sparse, heterogeneous clinical data

The ability to determine patient acuity (or severity of illness) has immediate practical use for clinicians. We evaluate the use of multivariate timeseries modeling with the multi-task Gaussian process (GP) models using noisy, incomplete, sparse, heterogeneous and unevenly-sampled clinical data, including both physiological signals and clinical notes. The learned multi-task GP (MTGP) hyperparameters are then used to assess and forecast patient acuity. Experiments were conducted with two real clinical data sets acquired from ICU patients: firstly, estimating cerebrovascular pressure reactivity, an important indicator of secondary damage for traumatic brain injury patients, by learning the interactions between intracranial pressure and mean arterial blood pressure signals, and secondly, mortality prediction using clinical progress notes. In both cases, MTGPs provided improved results: an MTGP model provided better results than single-task GP models for signal interpolation and forecasting (0.91 vs 0.69 RMSE), and the use of MTGP hyperparameters obtained improved results when used as additional classification features (0.812 vs 0.788 AUC).Intel Science and Technology Center for Big DataNational Institutes of Health. (U.S.). National Library of Medicine (Biomedical Informatics Research Training Grant NIH/NLM 2T15 LM007092-22)National Institute of Biomedical Imaging and Bioengineering (U.S.) (R01 Grant EB001659)Singapore. Agency for Science, Technology and Research (Graduate Scholarship