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Kimmo Kaski

Showing results (71-80 of 97) with videos related to

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Proceedings of the National Academy of Sciences of the United States of America|October 8, 2014
Reputation and impact in academic careersAlexander Michael Petersen, Santo Fortunato, Raj K Pan, et al.
Clinical and Translational Radiation Oncology|July 5, 2022
Auto-detection and segmentation of involved lymph nodes in HPV-associated oropharyngeal cancer using a convolutional deep learning neural networkNicolette Taku, Kareem A Wahid, Lisanne V van Dijk, et al.
Scientific Reports|August 29, 2023
Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT datasetJorma Järnstedt, Jaakko Sahlsten, Joel Jaskari, et al.
Plos One|June 25, 2024
Deep learning for 3D cephalometric landmarking with heterogeneous multi-center CBCT datasetJaakko Sahlsten, Jorma Järnstedt, Joel Jaskari, et al.
BMC Bioinformatics|May 12, 2007
A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic dataAki Vehtari, Ville-Petteri Mäkinen, Pasi Soininen, et al.
Seminars in Radiation Oncology|October 6, 2022
Artificial Intelligence for Radiation Oncology Applications Using Public DatasetsKareem A Wahid, Enrico Glerean, Jaakko Sahlsten, et al.
Scientific Reports|November 4, 2022
Comparison of deep learning segmentation and multigrader-annotated mandibular canals of multicenter CBCT scansJorma Järnstedt, Jaakko Sahlsten, Joel Jaskari, et al.
Frontiers in Oncology|March 17, 2023
Segmentation stability of human head and neck cancer medical images for radiotherapy applications under de-identification conditions: Benchmarking data sharing and artificial intelligence use-casesJaakko Sahlsten, Kareem A Wahid, Enrico Glerean, et al.
Atherosclerosis|May 30, 2006
The inherent accuracy of 1H NMR spectroscopy to quantify plasma lipoproteins is subclass dependentMika Ala-Korpela, Niko Lankinen, Aino Salminen, et al.
Journal of Lipid Research|September 8, 2009
Characterization of metabolic interrelationships and in silico phenotyping of lipoprotein particles using self-organizing mapsLinda S Kumpula, Sanna M Mäkelä, Ville-Petteri Mäkinen, et al.
Pageof 10

Showing results (71-80 of 97) with videos related to

Sort By:
Pageof 10
Proceedings of the National Academy of Sciences of the United States of America|October 8, 2014
Reputation and impact in academic careersAlexander Michael Petersen, Santo Fortunato, Raj K Pan, et al.
Clinical and Translational Radiation Oncology|July 5, 2022
Auto-detection and segmentation of involved lymph nodes in HPV-associated oropharyngeal cancer using a convolutional deep learning neural networkNicolette Taku, Kareem A Wahid, Lisanne V van Dijk, et al.
Scientific Reports|August 29, 2023
Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT datasetJorma Järnstedt, Jaakko Sahlsten, Joel Jaskari, et al.
Plos One|June 25, 2024
Deep learning for 3D cephalometric landmarking with heterogeneous multi-center CBCT datasetJaakko Sahlsten, Jorma Järnstedt, Joel Jaskari, et al.
BMC Bioinformatics|May 12, 2007
A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic dataAki Vehtari, Ville-Petteri Mäkinen, Pasi Soininen, et al.
Seminars in Radiation Oncology|October 6, 2022
Artificial Intelligence for Radiation Oncology Applications Using Public DatasetsKareem A Wahid, Enrico Glerean, Jaakko Sahlsten, et al.
Scientific Reports|November 4, 2022
Comparison of deep learning segmentation and multigrader-annotated mandibular canals of multicenter CBCT scansJorma Järnstedt, Jaakko Sahlsten, Joel Jaskari, et al.
Frontiers in Oncology|March 17, 2023
Segmentation stability of human head and neck cancer medical images for radiotherapy applications under de-identification conditions: Benchmarking data sharing and artificial intelligence use-casesJaakko Sahlsten, Kareem A Wahid, Enrico Glerean, et al.
Atherosclerosis|May 30, 2006
The inherent accuracy of 1H NMR spectroscopy to quantify plasma lipoproteins is subclass dependentMika Ala-Korpela, Niko Lankinen, Aino Salminen, et al.
Journal of Lipid Research|September 8, 2009
Characterization of metabolic interrelationships and in silico phenotyping of lipoprotein particles using self-organizing mapsLinda S Kumpula, Sanna M Mäkelä, Ville-Petteri Mäkinen, et al.
Pageof 10