Sökning: "Random Early Detection"

Visar resultat 1 - 5 av 18 uppsatser innehållade orden Random Early Detection.

1. 1. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Love Marcus; [2023]
   Nyckelord :User churn; Customer attrition; Artificial neural networks; Log-level analysis; Random forests; Decision trees; Användarbortfall; Kundbortfall; Artificiella neurala nätverk; logganalys; Slumpskogar; Beslutsträd;

   Sammanfattning : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. LÄS MER

3. 2. Automated Interpretation of Lung Ultrasound for COVID-19 and Tuberculosis diagnosis

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Chloé Soormally; [2023]
   Nyckelord :Tuberculosis; COVID-19; Lung Ultrasound; Computer-aided detection CAD ; Deep learning; Technology and Engineering;

   Sammanfattning : BACKGROUND. Early and accurate detection of infectious respiratory diseases like COVID-19 and tuberculosis (TB) plays a crucial role in effective management and the reduction of preventable mortality. LÄS MER

4. 3. Qualitative Image Selection with Active Learning

   Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

   Författare :Linnea Allander; Torben Nordtorp; [2023]
   Nyckelord :Technology and Engineering;

   Sammanfattning : In this work, an active learning pipeline is presented that allows for comparative tests between 3 different types of data scoring methods, uncertainty selection, diversity selection, and loss selection. Tests and parameter sweeps indicate that hyperparameters like reshuffling and early stopping are required to ensure fair comparisons. LÄS MER

5. 4. Predicting Chronic Kidney Disease using a multimodal Machine Learning approach

   Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Aakruti Mishra; Navaneeth Puthiyandi; [2023]
   Nyckelord :Chronic kidney disease; Multimodal approach; ROCKET; Random Forest; XGBoost; MIMIC-III database; Data imbalance; Temporal and static modalities; Soft voting;

   Sammanfattning : Chronic Kidney Disease (CKD) is a common and dangerous health condition that requires early detection and treatment to be effective. Current diagnostic methods are time-consuming and expensive. In this research, we hope to construct a predictive model for CKD utilizing a combination of time series and static variables for early detection of CKD. LÄS MER

7. 5. Thrombotic events in Covid-19 patients using Meta-Analysis

   Magister-uppsats, Högskolan i Skövde/Institutionen för biovetenskap

   Författare :Ugonna Okeke; [2022]
   Nyckelord :;

   Sammanfattning : Corona virus disease caused by severe acute respiratory virus 2 causes blockage of the blood vessel which leads to thrombosis. Thrombotic events in covid-19 patients results to hospitalizations and death. And incidence of thrombosis in covid-19 patients have been increasing in most regions of the world. LÄS MER