Sökning: "Survival models"
Visar resultat 6 - 10 av 158 uppsatser innehållade orden Survival models.
6. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells in the brain. The brain is responsible for regulating the functions of all other organs, hence, any atypical growth of cells in the brain can have severe implications for its functions. LÄS MER
7. Unveiling the Influence of Organizational Culture on Innovation in Family Businesses : Lessons from Sweden and Italy
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/FöretagsekonomiSammanfattning : Family businesses are a significant part of the global economy, contributing to employment and GDP growth. However, they face challenges in a dynamic and competitive landscape, requiring a shift in traditional approaches and a focus on innovation. LÄS MER
8. Predicting heart failure emergency readmissions
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Recent progress in treatment interventions has resulted in increased survival rates and longevity for diagnosed heart failure patients. However, heart failure still remains one of the leading causes of rehospitalization worldwide, where emergency readmissions continue to be a common occurrence. LÄS MER
9. Integrating web data miningand machine learningalgorithms to predict progression free survival and overall survival in multiple myeloma patients
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Multiple myeloma patients have highly variable progression free survival and overall survivalranging from a few weeks to more than 5 years. Stratification of these patients can help toidentify high risk patients i-e patients with short-term progression free survival and overallsurvival. LÄS MER
10. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. LÄS MER