Sökning: "Performance in healthcare"

Visar resultat 1 - 5 av 284 uppsatser innehållade orden Performance in healthcare.

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

   Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Författare :Nikolaos Staikos; [2024]
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

3. 2. The language of risk: A quantitative study on the effects of presentation format in risk communication

   C-uppsats, Handelshögskolan i Stockholm/Institutionen för marknadsföring och strategi

   Författare :Andreas Lidin; Daniel Mira; [2024]
   Nyckelord :Risk Communication; Numeracy; Presentation Format; Natural Frequencies;

   Sammanfattning : Consumers are faced with everyday decisions requiring understanding and interpretation of risks and probabilities. One area where the importance of good risk communication is particularly salient is in modern healthcare where shared medical decision making is a central feature. LÄS MER

4. 3. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder

   Kandidat-uppsats, Lunds universitet/Fysiska institutionen

   Författare :Max Svensson; [2024]
   Nyckelord :Machine Learning; Self-supervised learning; AI; Physics; Medicine; Physics and Astronomy;

   Sammanfattning : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. LÄS MER

5. 4. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network : Bildklassificering för hjärntumör medhjälp av förtränat konvolutionell tneuralt nätverk

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Ahmad Osman; Bushra Alsabbagh; [2023]
   Nyckelord :Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

   Sammanfattning : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells inthe 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 itsfunctions. The number of global mortality in 2020 led by cancerous brains was estimatedat 251,329. LÄS MER

7. 5. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network

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

   Författare :Bushra Alsabbagh; [2023]
   Nyckelord :Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

   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