Similarity metrics for surgical process models
| العنوان: | Similarity metrics for surgical process models |
|---|---|
| المؤلفون: | Frank Loebe, Pierre Jannin, Thomas Neumuth |
| المساهمون: | Innovation Center Computer Assisted Surgery (ICCAS), Universität Leipzig, Department of Computer Science [Leipzig], Institute for Medical Informatics, Statistics and Epidemiology [Leipzig] (IMISE), Vision, Action et Gestion d'informations en Santé (VisAGeS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Universität Leipzig [Leipzig], CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM) |
| المصدر: | Artificial Intelligence in Medicine Artificial Intelligence in Medicine, 2012, 54 (1), pp.15-27. ⟨10.1016/j.artmed.2011.10.001⟩ Artificial Intelligence in Medicine, Elsevier, 2012, 54 (1), pp.15-27. ⟨10.1016/j.artmed.2011.10.001⟩ |
| بيانات النشر: | Elsevier BV, 2012. |
| سنة النشر: | 2012 |
| مصطلحات موضوعية: | Models, Anatomic, Process modeling, Computer science, Medicine (miscellaneous), 02 engineering and technology, computer.software_genre, MESH: Models, Anatomic, Field (computer science), Workflow, MESH: Weights and Measures, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Task Performance and Analysis, 0202 electrical engineering, electronic engineering, information engineering, Decision Making, Computer-Assisted, Weights and measures, MESH: Decision Making, Computer-Assisted, MESH: Reproducibility of Results, Surgical process model, Surgery, Computer-Assisted, computer-assisted, MESH: Educational Measurement, [SDV.IB]Life Sciences [q-bio]/Bioengineering, 020201 artificial intelligence & image processing, Clinical Competence, MESH: Clinical Competence, Data mining, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Predictive validity, Process (engineering), MESH: Workflow, Set (abstract data type), 03 medical and health sciences, MESH: Computer Simulation, Similarity (network science), Artificial Intelligence, Humans, Computer Simulation, MESH: Humans, Reproducibility of Results, MESH: Task Performance and Analysis, MESH: Medical Informatics, Learning curve, Surgery, MESH: Surgery, Computer-Assisted, Educational Measurement, Decision making, computer, Medical Informatics |
| الوصف: | International audience; OBJECTIVE: The objective of this work is to introduce a set of similarity metrics for comparing surgical process models (SPMs). SPMs are progression models of surgical interventions that support quantitative analyses of surgical activities, supporting systems engineering or process optimization. METHODS AND MATERIALS: Five different similarity metrics are presented and proven. These metrics deal with several dimensions of process compliance in surgery, including granularity, content, time, order, and frequency of surgical activities. The metrics were experimentally validated using 20 clinical data sets each for cataract interventions, craniotomy interventions, and supratentorial tumor resections. The clinical data sets were controllably modified in simulations, which were iterated ten times, resulting in a total of 600 simulated data sets. The simulated data sets were subsequently compared to the original data sets to empirically assess the predictive validity of the metrics. RESULTS: We show that the results of the metrics for the surgical process models correlate significantly (p |
| تدمد: | 0933-3657 |
| DOI: | 10.1016/j.artmed.2011.10.001 |
| DOI: | 10.1016/j.artmed.2011.10.001⟩ |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0477174f82f9e85ab55dc1ed50978d19 https://doi.org/10.1016/j.artmed.2011.10.001 |
| Rights: | CLOSED |
| رقم الانضمام: | edsair.doi.dedup.....0477174f82f9e85ab55dc1ed50978d19 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 09333657 |
|---|---|
| DOI: | 10.1016/j.artmed.2011.10.001 |