Sökning: "kardiovaskulära modeller"
Hittade 5 uppsatser innehållade orden kardiovaskulära modeller.
1. Resultatet av distriktssköterskans/sjuksköterskans preventiva insatser för attminska risken för kardiovaskulär sjukdom hos patienter med hypertoni - En integrativ litteraturstudie
Magister-uppsats, Örebro universitet/Institutionen för hälsovetenskaperSammanfattning : Bakgrund: Hypertoni är en växande folksjukdom och den viktigaste riskfaktorn förutveckling av kardiovaskulär sjukdom, vilken utgör den största orsaken till sjukdomsbördaoch död globalt. Ohälsosamma levnadsvanor är riskfaktorer för utveckling av hypertoni ochkan förebyggas genom preventiva insatser. LÄS MER
2. 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
3. Parameter estimation in a cardiovascular computational model using numerical optimization : Patient simulation, searching for a digital twin
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Developing models of the cardiovascular system that simulates the dynamic behavior of a virtual patient’s condition is fundamental in the medical domain for predictive outcome and hypothesis generation. These models are usually described through Ordinary Differential Equation (ODE). LÄS MER
4. A Machine Learning Approach to the analysis of mortality in patients with cardiovascular diseases
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Cardiovascular diseases (CVDs) are the main cause of mortality worldwide, counting for a third of world demises. Consequently, early detection and underlying factors of these pathologies can play a critical role in successful treatments. Many researchers have applied machine learning (ML) for mortality risk estimation in CVDs. LÄS MER
5. A Comparison of Different Machine Learning Models for Cardiovascular Disease Detection
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Cardiovascular disease (CVD) is the leading cause of death worldwide and the majority of the deaths occur in low to middle income countries. This makes the prevention of CVDs an accute problem to study and much research has been done already. LÄS MER