Search for dissertations about: "machine learning methods"

Showing result 1 - 5 of 535 swedish dissertations containing the words machine learning methods.

2. 1. Machine learning for building energy system analysis

   Author : Fan Zhang; Johan Håkansson; Chris Bales; Stefan Byttner; Högskolan Dalarna; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; district heating; machine learning; deep learning; HVAC; neural networks;

   Abstract : Buildings account for approximately 40% of the global energy, and Heating, Ventilation, and Air Conditioning (HVAC) contributes to a large proportion of building energy consumption. Two main negative characteristics that contribute to performance degradation and energy waste in an HVAC system are inappropriate control strategies and faults. READ MORE

4. 2. Robust machine learning methods

   Author : Muhammad Osama; Dave Zachariah; Thomas B. Schön; Visa Koivunen; Uppsala universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; artificial intelligence; machine learning; risk minimization; data corruption; decision policy; conformal methods; data from contexts; online learning; spice; robust; causal inference; point process; localization; distribution uncertainty; treatment rules; quantile treatment; predicting count data; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

   Abstract : We are surrounded by data in our daily lives. The rent of our houses, the amount of electricity units consumed, the prices of different products at a supermarket, the daily temperature, our medicine prescriptions, our internet search history are all different forms of data. Data can be used in a wide range of applications. READ MORE

5. 3. Protein Model Quality Assessment : A Machine Learning Approach

   Author : Karolis Uziela; Arne Elofsson; Liam McGuffin; Stockholms universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Protein Model Quality Assessment; structural bioinformatics; machine learning; deep learning; support vector machine; proq; Artificial Neural Network; protein structure prediction; Biochemistry towards Bioinformatics; biokemi med inriktning mot bioinformatik;

   Abstract : Many protein structure prediction programs exist and they can efficiently generate a number of protein models of a varying quality. One of the problems is that it is difficult to know which model is the best one for a given target sequence. Selecting the best model is one of the major tasks of Model Quality Assessment Programs (MQAPs). READ MORE

6. 4. Visual Analytics for Explainable and Trustworthy Machine Learning

   Author : Angelos Chatzimparmpas; Andreas Kerren; Rafael M. Martins; Ilir Jusufi; Alex Endert; Linnéuniversitetet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; visualization; interaction; visual analytics; explainable machine learning; XAI; trustworthy machine learning; ensemble learning; dimensionality reduction; supervised learning; unsupervised learning; ML; AI; tabular data; visualisering; interaktion; visuell analys; förklarlig maskininlärning; XAI; pålitlig maskininlärning; ensembleinlärning; dimensionesreducering; övervakad inlärning; oövervakad inlärning; ML; AI; tabelldata; Computer Science; Datavetenskap; Informations- och programvisualisering; Information and software visualization;

   Abstract : The deployment of artificial intelligence solutions and machine learning research has exploded in popularity in recent years, with numerous types of models proposed to interpret and predict patterns and trends in data from diverse disciplines. However, as the complexity of these models grows, it becomes increasingly difficult for users to evaluate and rely on the model results, since their inner workings are mostly hidden in black boxes, which are difficult to trust in critical decision-making scenarios. READ MORE

7. 5. Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things : Enhancing COVID-19 & Early Sepsis Detection

   Author : Mahbub Ul Alam; Rahim Rahmani; Jaakko Hollmén; Sadok Ben Yahia; Stockholms universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Internet of Medical Things; Patient-Centric Healthcare; Clinical Decision Support System; Predictive Modeling in Healthcare; Health Informatics; Healthcare analytics; COVID-19; Sepsis; COVID-19 Detection; Early Sepsis Detection; Lung Segmentation Detection; Medical Data Annotation Scarcity; Medical Data Sparsity; Medical Data Heterogeneity; Medical Data Security Privacy; Practical Usability Enhancement; Low-End Device Adaptability; Medical Significance; Interpretability; Visualization; LIME; SHAP; Grad-CAM; LRP; Electronic Health Records; Thermal Image; Tabular Medical Data; Chest X-ray; Machine Learning; Deep Learning; Federated Learning; Semi-Supervised Machine Learning; Multi-Task Learning; Transfer Learning; Multi-Modality; Natural Language Processing; ClinicalBERT; GAN; data- och systemvetenskap; Computer and Systems Sciences;

   Abstract : This thesis presents a critical examination of the positive impact of Machine Learning (ML) and the Internet of Medical Things (IoMT) for advancing the Clinical Decision Support System (CDSS) in the context of COVID-19 and early sepsis detection.It emphasizes the transition towards patient-centric healthcare systems, which necessitate personalized and participatory care—a transition that could be facilitated by these emerging fields. READ MORE