Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Dennis Medved"'
Autor:
Paulo J. G. Lisboa, Manoj Jayabalan, Sandra Ortega-Martorell, Ivan Olier, Dennis Medved, Johan Nilsson
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract The most limiting factor in heart transplantation is the lack of donor organs. With enhanced prediction of outcome, it may be possible to increase the life-years from the organs that become available. Applications of machine learning to tabu
Externí odkaz:
https://doaj.org/article/a084c549767f4ffb98508f7e9b014075
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2022
Heart transplantation is a difficult procedure compared with other surgical operations, with a greater outcome uncertainty such as late rejection and death. We can model the success of heart transplants from predicting factors such as the age, sex, d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10968db61c08000e232c64fa04dbbbbf
https://pubmed.ncbi.nlm.nih.gov/36086591
https://pubmed.ncbi.nlm.nih.gov/36086591
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030399504
FoIKS
FoIKS
In this paper, we describe the conversion of three different heart transplantation data sets to a Resource Description Framework (RDF) representation and how it can be utilized to train deep learning models. These models were used to predict the outc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::011adb4b3196b428de1e828b38e20db4
https://doi.org/10.1007/978-3-030-39951-1_11
https://doi.org/10.1007/978-3-030-39951-1_11
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-9 (2018)
Scientific Reports
Scientific Reports
The primary objective of this study is to compare the accuracy of two risk models, International Heart Transplantation Survival Algorithm (IHTSA), developed using deep learning technique, and Index for Mortality Prediction After Cardiac Transplantati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c34bf6207a7eed8da5f6cae27814cd49
http://link.springer.com/article/10.1038/s41598-018-21417-7
http://link.springer.com/article/10.1038/s41598-018-21417-7
Publikováno v:
EMBC
We created a system to simulate the heart allocation process in a transplant queue, using a discrete event model and a neural network algorithm, which we named the Lund Deep Learning Transplant Algorithm (LuDeLTA). LuDeLTA is utilized to predict the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::445479516856c0f83d18a9b5c958bdc0
https://pubmed.ncbi.nlm.nih.gov/30441736
https://pubmed.ncbi.nlm.nih.gov/30441736
Autor:
Dennis Medved
Publikováno v:
Lund University
The human brain can be seen as an ensemble of interconnected neurons, more or less specialized to solve different cognitive and motor tasks. In computer science, the term deep learning is often applied to signify sets of interconnected nodes, where d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::668b124d941361dcb50c218fc13dee4f
https://lup.lub.lu.se/record/47d65dd7-6a15-4684-b579-d85287278ab9
https://lup.lub.lu.se/record/47d65dd7-6a15-4684-b579-d85287278ab9
Publikováno v:
EMBC
Heart transplantations have made it possible to extend the median survival time to 12 years for patients with end-stage heart diseases. This operation is unfortunately limited by the availability of donor organs and patients have to wait on average a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7490e88c3472f983b10bdede412478ed
https://pubmed.ncbi.nlm.nih.gov/29059814
https://pubmed.ncbi.nlm.nih.gov/29059814
Publikováno v:
EMBC
Heart transplantation (HT) is a life saving procedure, but a limited donor supply forces the surgeons to prioritize the recipients. The understanding of factors that predict mortality could help the doctors with this task. The objective of this study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::797401de09bef68a08a8b2f8c8b03d13
https://pubmed.ncbi.nlm.nih.gov/28269008
https://pubmed.ncbi.nlm.nih.gov/28269008
Publikováno v:
The Journal of Heart and Lung Transplantation. 37:S171-S172
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07ca17b8e7a42c59bb5fc7a998735d71
https://doi.org/10.1016/j.healun.2018.01.417
https://doi.org/10.1016/j.healun.2018.01.417
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319255293
ICPRAM (Selected Papers)
ICPRAM (Selected Papers)
In this article, we describe a system that classifies relations between entities extracted from an image. We started from the idea that we could utilize lexical and semantic information from text associated with the image, such as captions or surroun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec8525d0eec533ff2605b11830af6dc8
https://doi.org/10.1007/978-3-319-25530-9_9
https://doi.org/10.1007/978-3-319-25530-9_9