Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Richard Ljuhar"'
Autor:
Rosmarie Breu, Carolina Avelar, Zsolt Bertalan, Johannes Grillari, Heinz Redl, Richard Ljuhar, Stefan Quadlbauer, Thomas Hausner
Publikováno v:
Bone & Joint Research, Vol 13, Iss 10, Pp 588-595 (2024)
Aims: The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physi
Externí odkaz:
https://doaj.org/article/467a4d54a3e94e08a4a3e60f84ceacde
Autor:
Holden Archer, Seth Reine, Ahmed Alshaikhsalama, Joel Wells, Ajay Kohli, Louis Vazquez, Allan Hummer, Matthew D. DiFranco, Richard Ljuhar, Yin Xi, Avneesh Chhabra
Publikováno v:
Bone & Joint Open, Vol 3, Iss 11, Pp 877-884 (2022)
AimsHip dysplasia (HD) leads to premature osteoarthritis. Timely detection and correction of HD has been shown to improve pain, functional status, and hip longevity. Several time-consuming radiological measurements are currently used to confirm HD. A
Externí odkaz:
https://doaj.org/article/f4ff5c9d311149818cd2fd535a0ebc59
Autor:
Ahmad Almhdie-Imjabbar, Pawel Podsiadlo, Richard Ljuhar, Rachid Jennane, Khac-Lan Nguyen, Hechmi Toumi, Simo Saarakkala, Eric Lespessailles
Publikováno v:
Arthritis Research & Therapy, Vol 23, Iss 1, Pp 1-13 (2021)
Abstract Background Trabecular bone texture analysis (TBTA) has been identified as an imaging biomarker that provides information on trabecular bone changes due to knee osteoarthritis (KOA). Consequently, it is important to conduct a comprehensive re
Externí odkaz:
https://doaj.org/article/d31019d4d3b34b75b2048aa8bc50365b
Autor:
Seth Reine, Holden Archer, Ahmed Alshaikhsalama, Joel E Wells, Ajay Kohli, Louis Vazquez, Allan Hummer, Matthew D. Difranco, Richard Ljuhar, Yin Xi, Avneesh Chhabra
Publikováno v:
Advances in Artificial Intelligence and Machine Learning. :540-556
Background: Hip dysplasia (HD) causes accelerated osteoarthrosis of the acetabulum and is diagnosed through radiographic evaluation. An artificial intelligence (AI) program capable of measuring the necessary anatomical landmarks relevant to HD could
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f45e0d784e9a0c50c4964c18811f24ad
https://doi.org/10.54364/aaiml.2022.1137
https://doi.org/10.54364/aaiml.2022.1137
Publikováno v:
In Procedia CIRP 2014 21:467-472
Autor:
Maria Anna Smolle, Christoph Goetz, Dietmar Maurer, Ines Vielgut, Michael Novak, Gerhard Zier, Andreas Leithner, Stefan Nehrer, Tiago Paixao, Richard Ljuhar, Patrick Sadoghi
Publikováno v:
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA.
Purpose The aims of this study were to (1) analyze the impact of an artificial intelligence (AI)-based computer system on the accuracy and agreement rate of board-certified orthopaedic surgeons (= senior readers) to detect X-ray features indicative o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::528a06197c0367a7f5e2cc45e78142f0
https://pubmed.ncbi.nlm.nih.gov/36357505
https://pubmed.ncbi.nlm.nih.gov/36357505
Autor:
Markus Neubauer, Lukas Moser, Johannes Neugebauer, Marcus Raudner, Barbara Wondrasch, Magdalena Führer, Robert Emprechtinger, Dietmar Dammerer, Richard Ljuhar, Christoph Salzlechner, Stefan Nehrer
Publikováno v:
Journal of Clinical Medicine; Volume 12; Issue 3; Pages: 744
Background: Radiographic knee osteoarthritis (OA) severity and clinical severity are often dissociated. Artificial intelligence (AI) aid was shown to increase inter-rater reliability in radiographic OA diagnosis. Thus, AI-aided radiographic diagnoses
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b6ede978ea9d6b5408e77ae5f28e000
https://doi.org/10.3390/jcm12030744
https://doi.org/10.3390/jcm12030744
Autor:
Richard Ljuhar, Khac-Lan Nguyen, Rachid Jennane, Pawel Podsiadlo, Hechmi Toumi, Eric Lespessailles, A. Almhdie-Imjabbar, Simo Saarakkala
Publikováno v:
Arthritis Research & Therapy
Arthritis Research & Therapy, Vol 23, Iss 1, Pp 1-13 (2021)
Arthritis Research & Therapy, Vol 23, Iss 1, Pp 1-13 (2021)
Background Trabecular bone texture analysis (TBTA) has been identified as an imaging biomarker that provides information on trabecular bone changes due to knee osteoarthritis (KOA). Consequently, it is important to conduct a comprehensive review that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cce1dabc4f12c096a1e5f28609192fa1
https://doi.org/10.1186/s13075-021-02594-9
https://doi.org/10.1186/s13075-021-02594-9
Autor:
Prof. Dr. Fritz Scheuch, Prof. Dr. Rainer Hasenauer, Prof. Dr. Herbert Störi, Dr. Markus Pietzka, Dr. Wolfgang Schildorfer, Prof. Dr. Peter Filo, Prof. Dr. Jaroslav Jerz, Dr. Jozef Orgonaš, Prof. Dr. Milan Sokol, Mag. Anna Bohrn, Mag. Stefan Gratzl, Dipl.-Ing. Davul Ljuhar, Dr. Richard Ljuhar, Schön, Christian, Descovich, Philipp, Dr. Michael Gervautz, Mag. Norbert Zimmermann, MA Michael Kieslinger, Dr. Sabine Jung-Waclik, Dr. Thomas Wirth, Arens, Isabel, Bovenkamp, Daniele, Fessler, Jeremias, Holzer, Lisa, Klee, Günther, Krösen, Marco, Maurer, Alexander, Metzker, Roman, Patak, Johannes, Prácser, Lilla, Rodharth, Katharina, Schloffer, Stefanie, Scholz, Charlotte, Paholková, Barbora
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c3cab65a98f8574251bc0dcdf257b93
