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Visar resultat 1 - 5 av 210 uppsatser som matchar ovanstående sökkriterier.

1. 1. Predicting True Sepsis and Culture-positive Sepsis in Intensive Care Unit with Machine Learning Techniques

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Zeyuan Wu; [2024]
   Nyckelord :Machine Learning; Diagnosis of Sepsis; XGBoost; Logistic Regression; Mathematics and Statistics;

   Sammanfattning : Sepsis, a serious medical condition often leading to patients requiring intensive care, has prompted numerous scientists to employ mathematical techniques to aid in its diagnosis. This thesis uses logistic regression and a machine learning technique, XGBoost, to predict true sepsis (as opposed to sepsis mimics) and culture-positive sepsis (among true sepsis) in critical care using blood test results, physiological measurements and other patient characteristics. LÄS MER

3. 2. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Marisa Wodrich; [2024]
   Nyckelord :Uncertainty quantification; Deep learning; Breast cancer classification; Trustworthy AI; Point-of-care ultrasound; Mathematics and Statistics;

   Sammanfattning : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. LÄS MER

4. 3. Audio Anomaly Detection in Cars

   Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

   Författare :Asma Hussein; [2023-09-11]
   Nyckelord :Audio Anomaly detection; Outlier detection; Machine learning; Mel Frequency; Chroma;

   Sammanfattning : Audio anomaly detection in the context of car driving is a crucial task for ensuring vehicle safety and identifying potential faults. This paper aims to investigate and compare different methods for unsupervised audio anomaly detection using a data set consisting of recorded audio data from fault injections and normal "no fault" driving. LÄS MER

5. 4. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring

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

   Författare :Robert Iain Salter; [2023]
   Nyckelord :Behavioural Credit Scoring; Deep Learning; Machine Learning; Long Short-Term Memory; Default Prediction;

   Sammanfattning : Credit scoring is critical for banks to evaluate new loan applications and monitor existing customers. Machine learning has been extensively researched for this case; however, the adoption of machine learning methods is minimal in financial risk management. LÄS MER

7. 5. Few-Shot Learning for Quality Inspection

   Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Jesper Palmér; Ahmad Alsalehy; [2023]
   Nyckelord :Few-Shot Learning; AI; Transformers; ViT Deviation; Vision Transformers;

   Sammanfattning : The goal of this project is to find a suitable Few-Shot Learning (FSL) model that can be used in a fault detection system for use in an industrial setting. A dataset of Printed Circuit Board (PCB) images has been created to train different FSL models. LÄS MER