Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Ali Sharif Razavian"'
Autor:
Ehsan Akbarian, Mehrgan Mohammadi, Emilia Tiala, Oscar Ljungberg, Ali Sharif Razavian, Martin Magnéli, Max Gordon
Publikováno v:
Acta Orthopaedica, Vol 95 (2024)
Background and purpose: Artificial intelligence (AI) has the potential to aid in the accurate diagnosis of hip fractures and reduce the workload of clinicians. We primarily aimed to develop and validate a convolutional neural network (CNN) for the au
Externí odkaz:
https://doaj.org/article/cdab9791f92d4f2c8656036f25d681d4
Publikováno v:
BMC Musculoskeletal Disorders, Vol 22, Iss 1, Pp 1-8 (2021)
Abstract Background Prevalence for knee osteoarthritis is rising in both Sweden and globally due to increased age and obesity in the population. This has subsequently led to an increasing demand for knee arthroplasties. Correct diagnosis and classifi
Externí odkaz:
https://doaj.org/article/45734496c9f9453d9563d74a8e5c637a
Autor:
Anna Lind, Ehsan Akbarian, Simon Olsson, Hans Nåsell, Olof Sköldenberg, Ali Sharif Razavian, Max Gordon
Publikováno v:
PLoS ONE, Vol 16, Iss 4, p e0248809 (2021)
BackgroundFractures around the knee joint are inherently complex in terms of treatment; complication rates are high, and they are difficult to diagnose on a plain radiograph. An automated way of classifying radiographic images could improve diagnosti
Externí odkaz:
https://doaj.org/article/82b04b59958b4b9ea32a13da49efe8f9
Autor:
Jakub Olczak, Niklas Fahlberg, Atsuto Maki, Ali Sharif Razavian, Anthony Jilert, André Stark, Olof Sköldenberg, Max Gordon
Publikováno v:
Acta Orthopaedica, Vol 88, Iss 6, Pp 581-586 (2017)
Background and purpose — Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never bee
Externí odkaz:
https://doaj.org/article/535a85f3c85244a987b3b0e7c5fcdeb1
Publikováno v:
Acta Orthopaedica, Vol 92, Iss 1, Pp 102-108 (2020)
Acta Orthopaedica
article-version (VoR) Version of Record
Acta Orthopaedica
article-version (VoR) Version of Record
Background and purpose — Classification of ankle fractures is crucial for guiding treatment but advanced classifications such as the AO Foundation/Orthopedic Trauma Association (AO/OTA) are often too complex for human observers to learn and use. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11a8a4d1878384fe010c5e2acb6e797b
https://doaj.org/article/b6a49c2925c54bd6973ea961fdc3191c
https://doaj.org/article/b6a49c2925c54bd6973ea961fdc3191c
Publikováno v:
BMC Musculoskeletal Disorders
BMC Musculoskeletal Disorders, Vol 22, Iss 1, Pp 1-8 (2021)
BMC Musculoskeletal Disorders, Vol 22, Iss 1, Pp 1-8 (2021)
Background Prevalence for knee osteoarthritis is rising in both Sweden and globally due to increased age and obesity in the population. This has subsequently led to an increasing demand for knee arthroplasties. Correct diagnosis and classification of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79ab783fe54cf266575dc3f19556ec73
https://doi.org/10.1186/s12891-021-04722-7
https://doi.org/10.1186/s12891-021-04722-7
BACKGROUNDPrevalence for knee osteoarthritis is rising in Sweden and globally due to an ageing and more obese population. This has subsequently led to an increasing demand for knee arthroplasties. Correctly diagnosing, classifying, follow-up and plan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60cfc9eb20066d5aec7ba3a56acad843
https://doi.org/10.21203/rs.3.rs-154385/v1
https://doi.org/10.21203/rs.3.rs-154385/v1
Autor:
Niklas Fahlberg, Olof Sköldenberg, Jakub Olczak, Anthony Jilert, André Stark, Atsuto Maki, Ali Sharif Razavian, Max Gordon
Publikováno v:
Acta Orthopaedica, Vol 88, Iss 6, Pp 581-586 (2017)
Background and purpose — Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never bee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8685ef1929354ecbcb60fba734095ed7
https://doi.org/10.1080/17453674.2017.1344459
https://doi.org/10.1080/17453674.2017.1344459
Publikováno v:
ITE Transactions on Media Technology and Applications. 4:251-258
This paper provides an extensive study on the availability of image representations based on convolutional networks (ConvNets) for the task of visual instance retrieval. Besides the choice of convo ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e53777d96fb271aa49c0e4b12a31992
https://doi.org/10.3169/mta.4.251
https://doi.org/10.3169/mta.4.251
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence. 38(9)
Evidence is mounting that Convolutional Networks (ConvNets) are the most effective representation learning method for visual recognition tasks. In the common scenario, a ConvNet is trained on a large labeled dataset (source) and the feed-forward unit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa0a713d31f718f92adc8fda613d8e7e
https://pubmed.ncbi.nlm.nih.gov/26584488
https://pubmed.ncbi.nlm.nih.gov/26584488