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Artykuły w czasopismach na temat "Intelligence artificielle – Emploi en diagnostic"
EZANNO, Pauline, Sébastien PICAULT, Nathalie WINTER, Gaël BEAUNÉE, Hervé MONOD i Jean-François GUÉGAN. "Intelligence artificielle et santé animale". INRAE Productions Animales 33, nr 2 (15.09.2020): 95–108. http://dx.doi.org/10.20870/productions-animales.2020.33.2.3572.
Pełny tekst źródłaBastardot, François, i David Gachoud. "Le diagnostic visuel : au carrefour de la pédagogie médicale et des progrès en intelligence artificielle". Revue Médicale Suisse 15, nr 672 (2019): 2145–49. http://dx.doi.org/10.53738/revmed.2019.15.672.2145.
Pełny tekst źródłaKelly, Julia, Raoua Ben Messaoud, Marie Joyeux Faure, Robin Terrail, Renaud Tamisier, Jean-Benoît Martinot, Nhat Nam Le-Dong, Mary Morell i Jean-Louis Pepin. "Diagnostic du syndrome d’apnées du sommeil par un capteur mandibulaire associé à une analyse en intelligence artificielle versus la polysomnographie". Médecine du Sommeil 19, nr 1 (marzec 2022): 58. http://dx.doi.org/10.1016/j.msom.2022.01.018.
Pełny tekst źródłaGOCKO, X. "DALI". EXERCER 31, nr 168 (1.12.2020): 435. http://dx.doi.org/10.56746/exercer.2020.168.435.
Pełny tekst źródłaPIECHOWIAK, Sylvain. "Intelligence artificielle et diagnostic". Automatique et ingénierie système, marzec 2020. http://dx.doi.org/10.51257/a-v2-s7217.
Pełny tekst źródłaPIECHOWIAK, Sylvain. "Intelligence artificielle et diagnostic". Technologies logicielles Architectures des systèmes, grudzień 2003. http://dx.doi.org/10.51257/a-v1-s7217.
Pełny tekst źródłaGosselin, Laura, Maxime Thibault, Denis Lebel i Jean-François Bussières. "Utilisation de l’intelligence artificielle en pharmacie : une revue narrative". Canadian Journal of Hospital Pharmacy 74, nr 2 (19.04.2021). http://dx.doi.org/10.4212/cjhp.v74i2.3100.
Pełny tekst źródłaGong, Lingli, Anshuman Sharma, Mohammad Abdul Bhuiya, Hilmy Awad i Mohamed Z. Youssef. "An Adaptive Fault Diagnosis of Electric Vehicles: An Artificial Intelligence Blended Signal Processing Methodology Diagnostic adaptatif des défauts des véhicules électriques: Une méthodologie de traitement du signal combinée à l’intelligence artificielle". IEEE Canadian Journal of Electrical and Computer Engineering, 2023, 1–11. http://dx.doi.org/10.1109/icjece.2023.3264852.
Pełny tekst źródłaCockx, Bart, Koen Declercq, Muriel Dejemeppe i Bruno Van der Linden. "Focus 24 - avril 2020". Regards économiques, 16.07.2020. http://dx.doi.org/10.14428/regardseco2020.04.02.01.
Pełny tekst źródłaAdmin - JAIM. "Résumés des conférences JRANF 2021". Journal Africain d'Imagerie Médicale (J Afr Imag Méd). Journal Officiel de la Société de Radiologie d’Afrique Noire Francophone (SRANF). 13, nr 3 (17.11.2021). http://dx.doi.org/10.55715/jaim.v13i3.240.
Pełny tekst źródłaRozprawy doktorskie na temat "Intelligence artificielle – Emploi en diagnostic"
Carette, Romuald. "Détection automatisée du trouble du spectre de l'autisme via eye-tracking et réseaux de neurones artificiels : conception d'un système d'aide à la décision". Electronic Thesis or Diss., Amiens, 2020. http://www.theses.fr/2020AMIE0025.
Pełny tekst źródłaThe Computer Sciences and Psychology fields are very far from each other. However, some needs in Cognitive Psychology (CP) can be satisfied through the use of Artificial Intelligence (AI), in particular its connectionist approaches. There are a few uses of AI principles in CP, but they are quite inconspicuous. In particular, the case of the diagnosis support applied to Autism Spectrum Disorder (ASD) is a blank slate, with a few exceptions. As some work in CP show a great difference between some autistic traits and the ability to focus, notably visually, we have worked on data from an Eye-Tracker to try and detect young children with ASD apart from others without ASD of equivalent age. This data is of two distinct formats, on one hand based on the strict recording of the eyes positions on the screen (2 dimensions) and from the screen (3 dimensions), and on the other hand based on an automatic analysis of the eye sight dynamics. These two data types are digital models of information, generally read via a graphical plot over a video, by CP experts while observing their participants. The work in this thesis have focused on the application of various data modifications (presented as images, with a dimension reduction or statistics). It used various AI models (Artificial, Recurrent and Convolutional Neural Networks) to produce detection support techniques. Then, we have applied a weighted mean over these results to increase the precision of this detection support technique. Through the work conducted in this thesis, various approaches have been tried, keeping as a common element the neural networks as learning tool. Starting with a study about eye focus event and LSTM, we continued with ocular recorded raw data and a image-based modeling, used with a CNN. After applying PCA on these images, this data are also used with a simple ANN, with enhanced results. Then, a statistical study aims for the study of correlation between the values recorded by our Eye-Tracking device, the correlation are then given to an ANN to reach the highest results of this work. Finally, we tried to gather the information of some of these models to improve the obtained results once more.The best of our results allowed to produce a ROC curve with an AUC reaching 95%, which allow to think about an almost perfect support, given we could add some data used in manual diagnosis, and a complete freeing of the experts' time to enable a total focus on the setup of the child's support and his/her closer following. Moreover, the opportunity of an earlier child diagnosis can help better reducing the child's neurodevelopmental delay. None of these models are perfect. Still, there is to be noted that the diagnosis is never made, in practice, with the sole Eye-Tracking related data. Aiming to constitute a diagnosis support system, it essentially serves as a guiding tool for the professional in his/her work and to free a part of his/her time
Taleb, Catherine. "Parkinson's desease detection by multimodal analysis combining handwriting and speech signals". Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT039.
Pełny tekst źródłaParkinson’s disease (PD) is a neurological disorder caused by a decreased dopamine level on the brain. This disease is characterized by motor and non-motor symptoms that worsen over time. In advanced stages of PD, clinical diagnosis is clear-cut. However, in the early stages, when the symptoms are often incomplete or subtle, the diagnosis becomes difficult and at times, the subject may remain undiagnosed. Furthermore, there are no efficient and reliable methods capable of achieving PD early diagnosis with certainty. The difficulty in early detection is a strong motivation for computer-based assessment tools/decision support tools/test instruments that can aid in the early diagnosing and predicting the progression of PD.Handwriting’s deterioration and vocal impairment may be ones of the earliest indicators for the onset of the illness. According to the reviewed literature, a language independent model to detect PD using multimodal signals has not been enough addressed. The main goal of this thesis is to build a language independent multimodal system for assessment the motor disorders in PD patients at an early stage based on combined handwriting and speech signals, using machine learning techniques. For this purpose and due to the lack of a multimodal and multilingual dataset, such database that is equally distributed between controls and PD patients was first built. The database includes handwriting, speech, and eye movements’ recordings collected from control and PD patients in two phases (“on-state” and “off-state”). In this thesis we focused on handwriting and speech analysis, where PD patients were studied in their “on-state”.Language-independent models for PD detection based on handwriting features were built; where two approaches were considered, studied and compared: a classical feature extraction and classifier approach and a deep learning approach. Approximately 97% classification accuracy was reached with both approaches. A multi-class SVM classifier for stage detection based on handwriting features was built. The achieved performance was non-satisfactory compared to the results obtained for PD detection due to many obstacles faced.Another language and task-independent acoustic feature set for assessing the motor disorders in PD patients was built. We have succeeded to build a language independent SVM model for PD diagnosis through voice analysis with 97.62% accuracy. Finally, a language independent multimodal system for PD detection by combining handwriting and voice signals was built, where both classical SVM model and deep learning models were both analyzed. A classification accuracy of 100% is obtained when handcrafted features from both modalities are combined and applied to the SVM. Despite the encouraging results obtained, there is still some works to do before putting our PD detection multimodal model into clinical use due to some limitations inherent to this thesis
Ribas, Santos Eduardo. "Contribution au diagnostic qualitatif des procédés en intelligence artificielle". Vandoeuvre-les-Nancy, INPL, 1996. http://docnum.univ-lorraine.fr/public/INPL_T_1996_RIBAS_SANTOS_E.pdf.
Pełny tekst źródłaJaouen, Tristan. "Caractérisation du cancer de la prostate de haut grade à l’IRM multiparamétrique à l’aide d’un système de diagnostic assisté par ordinateur basé sur la radiomique et utilisé comme lecteur autonome ou comme second lecteur". Electronic Thesis or Diss., Lyon, 2022. http://www.theses.fr/2022LYSE1140.
Pełny tekst źródłaWe developed a region of interest-based (ROIs) computer-aided diagnosis system (CAD) to characterize International Society of Urological Pathology grade (ISUP) ≥2 prostate cancers at multiparametric MRI (mp-MRI). Image parameters from two multi-vendor datasets of 265 pre-prostatectomy and 112 pre-biopsy MRIs were combined using logistic regression. The best models used the ADC 2nd percentile (ADC2) and normalized wash-in rate (WI) in the peripheral zone (PZ) and the ADC 25th percentile (ADC25) in the transition zone (TZ). They were combined in the CAD system. The CAD was retrospectively assessed on two multi-vendor datasets containing respectively 158 and 105 pre-biopsy MRIs from our institution (internal test dataset) and another institution (external test dataset). Two radiologists independently outlined lesions targeted at biopsy. The Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) score prospectively assigned at biopsy and the CAD score were compared to biopsy findings. At patient level, the areas under the Receiver Operating Characteristic curve (AUC) of the PI-RADSv2 score were 82% (95% CI: 74-87) and 85% (95% CI: 79-91) in the internal and external test datasets respectively. For both radiologists, the CAD score had similar AUC results in the internal (82%, 95% CI: 76-89, p=1; 84%, 95% CI: 78-91, p=1) and external (82%, 95% CI: 76-89, p=0.82; 86%, 95% CI: 79-93, p=1) test datasets. Combining PI-RADSv2 and CAD findings could have avoided 41-52% of biopsies while missing 6-10% of ISUP≥2 cancers. The CAD system confirmed its robustness showing good discrimination of ISUP ≥2 cancers in a multicentric study involving 22 different scanners with highly heterogeneous image protocols. In per patient analysis, the CAD and the PI-RADSv2 had similar AUC values (76%, 95% CI: 70-82 vs 79%, 95% CI: 73-86; p=0.34) and sensitivities (86%, 95% CI: 76-96 vs 89%, 95% CI: 79-98 for PI-RADSv2 ≥4). The specificity of the CAD (62%, 95% CI: 53-70 vs 49%, 95% CI: 39-59 for PI-RADSv2 ≥4) could be used to complement the PI-RADSv2 score and potentially avoid 50% of biopsies, while missing 13% of ISUP ≥2 cancers. These findings were very similar to those reported in the single center test cohorts. Given its robustness, the CAD could then be exploited in more specific applications. The CAD first provided good discrimination of ISUP ≥2 cancers in patients under Active Surveillance. Its AUC (80%, 95% CI: 74-86) was similar to that of the PI-RADS score prospectively assigned by specialized uro-radiologists at the time of biopsy (81%, 95% CI: 74-87; p=0.96). After dichotomization, the CAD was more specific than the PI-RADS ≥3 (p<0.001) and the PI-RADS ≥4 scores (p<0.001). It could offer a solution to select patients who could safely avoid confirmatory or follow-up biopsy during Active Surveillance (25%), while missing 5% of ISUP≥2 cancers. Finally, the CAD was tested with the pre-prostatectomy mp-MRIs of 56 Japanese patients, from a population which is geographically distant from its training population and which is of interest because of its low prostate cancer incidence and mortality. The CAD obtained an AUC similar to the PI-RADSv2 score assigned by an experience radiologist in the PZ (80%, 95% CI: 71-90 vs 80%, 95% CI: 71-89; p=0.886) and in the TZ (79%, 95% CI: 66-90 vs 93%, 95%CI: 82-96; p=0.051). These promising and robust results across heterogeneous datasets suggest that the CAD could be used in clinical routine as a second opinion reader to help select the patients who could safely avoid biopsy. This CAD may assist less experience readers in the characterization of prostate lesions
Fabien, Aratbi-Perrot. "Diagnostic et suivi d'état embarqués -- Une étude algorithmique". Phd thesis, Université Paul Sabatier - Toulouse III, 2011. http://tel.archives-ouvertes.fr/tel-00864629.
Pełny tekst źródłaHamburger, Jean. "Intelligence artificielle et geologie : interpretation geo-historique et diagnostic de ceonception". Paris 6, 1990. http://www.theses.fr/1990PA066533.
Pełny tekst źródłaGerlinger, Gilles. "Diagnostic en temps réel par système expert : application à un système de diagnostic embarqué sur automobile". Compiègne, 1991. http://www.theses.fr/1991COMPD366.
Pełny tekst źródłaLarrechea, Michel. "Méthodologie de modélisation des connaissances dans le domaine du diagnostic technique". Bordeaux 1, 1995. http://www.theses.fr/1995BOR10651.
Pełny tekst źródłaEl, Falou Mohamad. "Contributions à la composition dynamique de services fondée sur des techniques de planification et diagnostic multi-agents". Caen, 2010. http://www.theses.fr/2010CAEN2015.
Pełny tekst źródłaThis thesis addresses the problem of service composition. We focus on the use of planning techniques and we introduce two different approaches that overcome some limitations of the existing approaches. The first approach has two centralized algorithms based respectively on Tree-seach and Graphplan. These algorithms do not scale up well due to their exponential complexity. In the second approach, we overcome this limitation by proposing a multi-agents planning architecture where each web service defined by a set of services and is considered as an agent. The agents are coordinated by merging their best partial plan that answer partially to a request. This coordination procedure is repeated iteratively until reaching the goal using a local heuristic function. This approach is then extended by a global heuristics to ensure its completeness if the sub-problems assigned to the agents are dependent. This global heuristic of evaluating the best local plan avoids the wells by considering the intermediate local plans offered by other agents. The study of the complexity of decentralized approaches shows that they are polynomial, and experimental results show that they are able to scale up well for complex problems. Finally, a self-healing services composition agent-based architecture is developed. This architecture is a real integration between the processes of composition, active dignosis, and repair into one planning process
Maalej, Mohamed-Amine, i Véronique Delcroix. "Diagnostic multiple des systèmes complexes à base de réseaux bayésiens". Valenciennes, 2006. http://ged.univ-valenciennes.fr/nuxeo/site/esupversions/46028b3e-dbca-41c6-a69f-b740ee4d0519.
Pełny tekst źródłaModel Based Diagnosis approach revolutionizes the field of the diagnosis as overcoming the lack of knowledge by using Model. Our research focuses on the task of multiple diagnosis, from failure observations, for complex and highly-reliable large systems. We take the advantages of the Bayesian networks models to improve the diagnosis of this type of systems. These models integrate the components failures prior probabilities, and allow estimating posterior probabilities of diagnoses, by an approached calculation. We present a methodology of diagnosis using Bayesian network. Our approach integrates a model design method, in addition to two diagnosis algorithms : the first algorithm allows calculating the most probable diagnoses for a failing system; the second provides quickly representatives of the diagnosis classes, it reveals also the cases while additional observations are necessary. Finally we test these algorithms in terms of computing time and results quality for digital circuits of various sizes
Książki na temat "Intelligence artificielle – Emploi en diagnostic"
Gmyrek, Pawel, Janine Berg i David Bescond. Intelligence artificielle générative et emploi. Genève: OIT, 2023. http://dx.doi.org/10.54394/cbqi1358.
Pełny tekst źródłaJean, Renaud, red. Raisonnement à partir de cas 2: Surveillance, diagnostic et maintenance. Paris: Hermes science, 2007.
Znajdź pełny tekst źródłaAshlesha, Jain, red. Artificial intelligence techniques in breast cancer diagnosis and prognosis. Singapore: World Scientific, 2000.
Znajdź pełny tekst źródłaauthor, Yun Kil-gŭn, i Pak Hyŏng-gŭn author, red. In'gong chinŭng sidae ŭi injae hyŏngmyŏng: Talent revolution in the age of artificial intelligence. Kyŏnggi-do P'aju-si: Kyoyuk Kwahaksa, 2021.
Znajdź pełny tekst źródłaProbabilistic similarity networks. Cambridge, Mass: MIT Press, 1991.
Znajdź pełny tekst źródłaMorra, Lia, Silvia Delsanto i Loredana Correale. Artificial Intelligence in Medical Imaging. Taylor & Francis Group, 2021.
Znajdź pełny tekst źródłaMorra, Lia, Silvia Delsanto i Loredana Correale. Artificial Intelligence in Medical Imaging: From Theory to Clinical Practice. Taylor & Francis Group, 2019.
Znajdź pełny tekst źródłaArtificial Intelligence in Medical Imaging: From Theory to Clinical Practice. Taylor & Francis Group, 2019.
Znajdź pełny tekst źródłaArtificial Intelligence in Medical Imaging: From Theory to Clinical Practice. Taylor & Francis Group, 2019.
Znajdź pełny tekst źródłaBhatia, Surbhi, i Kauser Hameed. Researches and Applications of Artificial Intelligence to Mitigate Pandemics: History, Diagnostic Tools, Epidemiology, Healthcare, and Technology. Elsevier Science & Technology, 2021.
Znajdź pełny tekst źródłaCzęści książek na temat "Intelligence artificielle – Emploi en diagnostic"
PULIDO, Belarmino, Carlos J. ALONSO-GONZÁLEZ i Anibal BREGON. "Approche par intelligence artificielle du diagnostic basé sur les modèles". W Diagnostic et commande à tolérance de fautes 1, 235–69. ISTE Group, 2024. http://dx.doi.org/10.51926/iste.9058.ch6.
Pełny tekst źródłaGreen, Andrew. "Intelligence artificielle et emploi : aucun signe de fléchissement de la demande de main-d’œuvre (pour l’instant)". W Perspectives de l’emploi de l’OCDE 2023. OECD, 2023. http://dx.doi.org/10.1787/25e21bcb-fr.
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