Sökning: "Blood loss"
Visar resultat 1 - 5 av 144 uppsatser innehållade orden Blood loss.
1. Förekommer förändringar i vätskebalansen hos hästar med EMS vid korttidsbehandling med en SGLT2-hämmare?
Master-uppsats, SLU/Dept. of Clinical SciencesSammanfattning : Ekvint metabolt syndrom (EMS) är ett sjukdomskomplex innefattande flertalet riskfaktorer för att utveckla endokrinologisk fång. Främst innebär EMS insulindysreglering (ID), vilket yttrar sig som hyperinsulinemi (onormalt höga koncentrationer av insulin i blodet). LÄS MER
2. Network Orientation and Segmentation Refinement Using Machine Learning
Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknikSammanfattning : Network mapping is used to extract the coordinates of a network's components in an image. Furthermore, machine learning algorithms have demonstrated their efficacy in advancing the field of network mapping across various domains, including mapping of road networks and blood vessel networks. LÄS MER
3. Effekten av liraglutid som monoterapi eller i kombination med metformin vid behandling av fetma och övervikt hos kvinnor med polycystiskt ovarialt syndrom
Kandidat-uppsats, Linnéuniversitetet/Institutionen för kemi och biomedicin (KOB)Sammanfattning : Introduction: Overweight and obesity are among the most serious public health problems in the world. Today, about half of adult men, one third of adult women and one in five children are estimated to be overweight or obese. LÄS MER
4. 3D geospatial data requirements for simulating noise using the Nord2000 model: Case study of the impact of building façade types and roof configurations on simulated traffic noise levels
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : The European Union implements the Environmental Noise Directive (END), which offers a framework for evaluating and assessing environmental noise. All EU members are required to create strategic noise maps to inform the public about noise pollution and its effects. LÄS MER
5. Explainable Machine Learning in Cardiovascular Diagnostics
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The major challenges in implementing machine learning models in medical applications stemfrom ethical and accountability concerns, which arise from the lack of insight and understandingof the models' inner workings and reasoning. This opaqueness has resulted in the emergenceof a new subfield of machine learning called Explainability, which aims to develop and deploymethods to gain insight into how input data is weighted and propagated through a machinelearning algorithm. LÄS MER