Essays about: "thesis in healthcare information"

Showing result 1 - 5 of 181 essays containing the words thesis in healthcare information.

1. 1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

   University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Author : Nikolaos Staikos; [2024]
   Keywords : Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

   Abstract : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. READ MORE

3. 2. Development of a System Dynamic Model of Mental Healthcare Structure in Stockholm

   University essay from KTH/Medicinteknik och hälsosystem

   Author : Julia Osswald; [2024]
   Keywords : Mental health; mental healthcare; healthcare structure; system dynamics; simulation; emergency care; modeling; primary care; specialized care; Stockholm; mental healthcare system; Psykisk hälsa; psykiatrisk vård; vårdstruktur; systemdynamisk modell; simulering; akutsjukvård; primärvård; specialiserad vård; psykiatriskt sjukvårdssystem; Stockholm.;

   Abstract : Mental illnesses are the leading cause of disability in the world today, affecting nearly a billion people including 14% of the world’s adolescents. Mental illnesses include both psychiatric conditions and inconveniences and is a broad term to describe multiple different conditions in varying severity. READ MORE

4. 3. Estimating Diffusion Tensor Distributions With Neural Networks

   University essay from Linköpings universitet/Algebra, geometri och diskret matematik; Linköpings universitet/Tekniska fakulteten

   Author : Rimaz Nismi; [2024]
   Keywords : Diffusion; Magnetic Resonance Imaging; MRI; Neural Networks; Optimal transport; Earth mover s distance; Sinkhorn distance;

   Abstract : Magnetic Resonance Imaging (MRI) is an essential healthcare technology, with diffusion MRI being a specialized technique. Diffusion MRI exploits the inherent diffusion of water molecules within the human body to produce a high-resolution tissue image. An MRI image contains information about a 3D volume in space, composed of 3D units called voxels. READ MORE

5. 4. A Decentralised Application for Storing Electronic Health Records using Blockchain Technology

   University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

   Author : Edenia Isaac; Hampus Jernkrook; NIls Johnsson; Christopher Molin; Wendy Pau; David Zamanian; [2023-03-03]
   Keywords : electronic health records; EHR; medical records; blockchain; Ethereum; IPFS; decentralised applications; Web3.Storage; information exchange; patientjournaler; blockkedja; decentraliserade applikationer; informationsdelning;

   Abstract : With the systems currently used in healthcare, medical records are often centrally stored in local databases or cloud services and managed by each individual healthcare provider. Due to this, the information exchange between healthcare providers is often limited. READ MORE

6. 5. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning

   University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Author : Ilya Ploshchik; [2023]
   Keywords : Visualization; interaction; metamodels; validation metrics; predicted probabilities; stacking; stacked generalization; ensemble learning; machine learning;

   Abstract : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. READ MORE