1,720,973 research outputs found
Oncolog-IA : symbolic and numeric artificial intelligence for learning complexity of breast cancer cases and providing decision support for their therapeutic management
No full textDe nombreux pays ont instauré l’organisation de réunions de concertation pluridisciplinaire (RCP) afin de promouvoir la décision collective des différents professionnels de santé impliqués dans la prise en charge des patients atteints de cancer. Cependant, l’impact des RCP sur la qualité des soins a été remis en cause car le bon fonctionnement des RCP est entravé par le manque de temps, la quantité des informations à gérer, et la complexité des cas discutés. Par ailleurs, les systèmes d’aide à la décision médical (SADM), ont le potentiel d’améliorer la qualité des décisions de prise en charge de cancer du sein, mais ils sont encore très peu utilisés en routine, notamment parce qu’ils ne sont pas en adéquation avec les attentes des cliniciens qui les utilisent. Oncolog-IA est un projet de recherche, qui vise à utiliser des méthodes d’intelligence artificielle numériques et symboliques pour l’apprentissage des cas complexes de cancer du sein à partir d'un corpus de documents incluant les fiches issues des RCP extraites de l’EDS de l’AP-HP. Les fiches RCP sont préalablement structurées par la mise en œuvre de techniques de traitement du langage naturel. Une fois l’apprentissage de la complexité établi, l’objectif du projet est de proposer deux systèmes d’aide à la décision selon la complexité des cas cliniques de cancer du sein : • Un système basé sur les guides de bonnes pratiques pour les cas non complexes • Un système basé sur un raisonnement par analogie pour les cas complexes, à travers le rappel des décision prises pour des cas similaires.Many countries have introduced multidisciplinary tumor boards (MTBs) to promote collective decision-making by the various health professionals involved in the management of cancer patients. However, the impact of MTBs on the quality of care has been questioned because the proper functioning of MTBs is hampered by the lack of time, the amount of information to be managed, and the complexity of cases discussed. On the other hand, clinical decision support systems (CDSSs) have the potential to improve the quality of breast cancer management decisions, but they are still not used in clinical routine, notably because they are not in line with the expectations of the clinicians who use them. Oncolog-IA is a research project, which aims at using numerical and symbolic artificial intelligence methods for learning complex breast cancer cases from a corpus of documents including breast cancer patient summaries (BCPSs) extracted from the datawarehouse of AP-HP hospitals. BCPS contents have been structured by implementing various natural language processing techniques, and algorithms were then trained to automatically detect the complexity of a breast cancer cases. Once the complexity has been learnt, the second objective of the project was to propose two decision support systems according to complexity: • A guideline based decision support system for non-complex cases ( we have reused the GL-DSS implemented in the DESIREE project ) • A cased-based decision support system for complex cases, through the recall of decisions taken for similar cases
Oncolog-IA : utilisation des méthodes d’intelligence artificielle pour la détection automatique des cas complexes de cancer du sein et l’aide à la décision pour leur prise en charge thérapeutique
No full textMany countries have introduced multidisciplinary tumor boards (MTBs) to promote collective decision-making by the various health professionals involved in the management of cancer patients. However, the impact of MTBs on the quality of care has been questioned because the proper functioning of MTBs is hampered by the lack of time, the amount of information to be managed, and the complexity of cases discussed. On the other hand, clinical decision support systems (CDSSs) have the potential to improve the quality of breast cancer management decisions, but they are still not used in clinical routine, notably because they are not in line with the expectations of the clinicians who use them. Oncolog-IA is a research project, which aims at using numerical and symbolic artificial intelligence methods for learning complex breast cancer cases from a corpus of documents including breast cancer patient summaries (BCPSs) extracted from the datawarehouse of AP-HP hospitals. BCPS contents have been structured by implementing various natural language processing techniques, and algorithms were then trained to automatically detect the complexity of a breast cancer cases. Once the complexity has been learnt, the second objective of the project was to propose two decision support systems according to complexity: • A guideline based decision support system for non-complex cases ( we have reused the GL-DSS implemented in the DESIREE project ) • A cased-based decision support system for complex cases, through the recall of decisions taken for similar cases.De nombreux pays ont instauré l’organisation de réunions de concertation pluridisciplinaire (RCP) afin de promouvoir la décision collective des différents professionnels de santé impliqués dans la prise en charge des patients atteints de cancer. Cependant, l’impact des RCP sur la qualité des soins a été remis en cause car le bon fonctionnement des RCP est entravé par le manque de temps, la quantité des informations à gérer, et la complexité des cas discutés. Par ailleurs, les systèmes d’aide à la décision médical (SADM), ont le potentiel d’améliorer la qualité des décisions de prise en charge de cancer du sein, mais ils sont encore très peu utilisés en routine, notamment parce qu’ils ne sont pas en adéquation avec les attentes des cliniciens qui les utilisent. Oncolog-IA est un projet de recherche, qui vise à utiliser des méthodes d’intelligence artificielle numériques et symboliques pour l’apprentissage des cas complexes de cancer du sein à partir d'un corpus de documents incluant les fiches issues des RCP extraites de l’EDS de l’AP-HP. Les fiches RCP sont préalablement structurées par la mise en œuvre de techniques de traitement du langage naturel. Une fois l’apprentissage de la complexité établi, l’objectif du projet est de proposer deux systèmes d’aide à la décision selon la complexité des cas cliniques de cancer du sein : • Un système basé sur les guides de bonnes pratiques pour les cas non complexes • Un système basé sur un raisonnement par analogie pour les cas complexes, à travers le rappel des décision prises pour des cas similaires
Oncolog-IA : utilisation des méthodes d’intelligence artificielle pour la détection automatique des cas complexes de cancer du sein et l’aide à la décision pour leur prise en charge thérapeutique
No full textMany countries have introduced multidisciplinary tumor boards (MTBs) to promote collective decision-making by the various health professionals involved in the management of cancer patients. However, the impact of MTBs on the quality of care has been questioned because the proper functioning of MTBs is hampered by the lack of time, the amount of information to be managed, and the complexity of cases discussed. On the other hand, clinical decision support systems (CDSSs) have the potential to improve the quality of breast cancer management decisions, but they are still not used in clinical routine, notably because they are not in line with the expectations of the clinicians who use them. Oncolog-IA is a research project, which aims at using numerical and symbolic artificial intelligence methods for learning complex breast cancer cases from a corpus of documents including breast cancer patient summaries (BCPSs) extracted from the datawarehouse of AP-HP hospitals. BCPS contents have been structured by implementing various natural language processing techniques, and algorithms were then trained to automatically detect the complexity of a breast cancer cases. Once the complexity has been learnt, the second objective of the project was to propose two decision support systems according to complexity: • A guideline based decision support system for non-complex cases ( we have reused the GL-DSS implemented in the DESIREE project ) • A cased-based decision support system for complex cases, through the recall of decisions taken for similar cases.De nombreux pays ont instauré l’organisation de réunions de concertation pluridisciplinaire (RCP) afin de promouvoir la décision collective des différents professionnels de santé impliqués dans la prise en charge des patients atteints de cancer. Cependant, l’impact des RCP sur la qualité des soins a été remis en cause car le bon fonctionnement des RCP est entravé par le manque de temps, la quantité des informations à gérer, et la complexité des cas discutés. Par ailleurs, les systèmes d’aide à la décision médical (SADM), ont le potentiel d’améliorer la qualité des décisions de prise en charge de cancer du sein, mais ils sont encore très peu utilisés en routine, notamment parce qu’ils ne sont pas en adéquation avec les attentes des cliniciens qui les utilisent. Oncolog-IA est un projet de recherche, qui vise à utiliser des méthodes d’intelligence artificielle numériques et symboliques pour l’apprentissage des cas complexes de cancer du sein à partir d'un corpus de documents incluant les fiches issues des RCP extraites de l’EDS de l’AP-HP. Les fiches RCP sont préalablement structurées par la mise en œuvre de techniques de traitement du langage naturel. Une fois l’apprentissage de la complexité établi, l’objectif du projet est de proposer deux systèmes d’aide à la décision selon la complexité des cas cliniques de cancer du sein : • Un système basé sur les guides de bonnes pratiques pour les cas non complexes • Un système basé sur un raisonnement par analogie pour les cas complexes, à travers le rappel des décision prises pour des cas similaires
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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