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Deep Learning Applications - From image analysis to medical diagnosis


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Titel: Deep Learning Applications - From image analysis to medical diagnosis
Författare: Helgadottir, Saga
E-post: saga.helgadottir@physics.gu.se
Utgivningsdatum: 11-maj-2021
Universitet: Göteborgs universitet. Naturvetenskapliga fakulteten
Institution: Department of Physics ; Institutionen för fysik
Delarbeten: Digital video microscopy enhanced by deep learning Saga Helgadottir, Aykut Argun and Giovanni Volpe Optica 6, 506-513 (2019)
VISA ARTIKEL


Quantitative Digital Microscopy with Deep Learning Benjamin Midtvedt, Saga Helgadottir, Aykut Argun, Jesús Pineda, Daniel Midtvedt and Giovanni Volpe Applied Physics Reviews 8, 011310 (2021)
VISA ARTIKEL


Extracting quantitative biological information from brightfield cell images using deep learning Saga Helgadottir, Benjamin Midtvedt, Jesús Pineda, Alan Sabirsh, Caroline B. Adiels, Stefano Romeo, Daniel Midtvedt and Giovanni Volpe arXiv preprint arXiv:2012.12986 (2020)

Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning Ana Pina, Saga Helgadottir, Rosellina Margherita Mancina, Chiara Pavanello, Carlo Pirazzi, Tiziana Montalcini, Roberto Henriques, Laura Calabresi, Olov Wiklund, M Paula Macedo, Luca Valenti, Giovanni Volpe and Stefano Romeo European Journal of Preventive Cardiology, p.2047487319898951 (2020)
VISA ARTIKEL


Enhanced prediction of atrial fibrillation and mortality among patients with congenital heart disease using big data and deep learning Kok Wai Giang , Saga Helgadottir, Mikael Dellborg, Giovanni Volpe and Zacharias Mandalenakis (submitted 2021)

Improving epidemic testing and containment strategies using machine learning Laura Natali, Saga Helgadottir, Onofrio M. Marago and Giovanni Volpe Machine Learning: Science and Technology (2021)
VISA ARTIKEL

Datum för disputation: 2021-06-16
Disputation: Onsdagen den 16 juni 2021, kl. 9:00, Hörsal PJ, Fysikgården 2b och via Zoom
Examinationsnivå: Doctor of Philosophy
Publikationstyp: Doctoral thesis
Nyckelord: deep learning
neural networks
image analysis
microscopy
medical diagnosis
Sammanfattning: Deep learning is a subcategory of machine learning and artificial intelligence. Instead of using explicit rules to perform a desired task as in standard algorithmic approaches, machine-learning algorithms autonomously learn from data to determine the rules for the task at hand. The idea of deep learning has been around since the 1950s but was for a long time limited by available computational power and amount of training data. Once overcome these problems, in recent years, deep learning has made... mer
ISBN: 978-91-8009-366-8
URI: http://hdl.handle.net/2077/67506
Samling:Doctoral Theses from University of Gothenburg / Doktorsavhandlingar från Göteborgs universitet
Doctoral Theses / Doktorsavhandlingar Institutionen för fysik

 

 

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