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您的检索式：作者名="Eric Hohmann"
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| 1 | TRANSLATING THE MULTI-ACTOR APPROACH TO RESEARCH INTO PRACTICE USING A WORKSHOP APPROACH FOCUSING ON SPECIES MIXTURES显示文摘The EIP-Agri multiactor approach was exemplified during a 3-day workshop with 63 project participants from the EU H2020 funded project“Redesigning European cropping systems based on species MIXtures”.The objective was to share firsthand experience of participatory research among researchers who were mostly not familiar with this approach.Workshop participants were divided into smaller multidisciplinary groups and given the opportunity to interact with representatives from eight actor positions in the value chain of the agrifood cooperative Terrena located in Western France.The four stages of the workshop were:(1)key actor interviews,(2)sharing proposed solutions for overcoming barriers,and(3)developing possible interdisciplinary concepts.Expressions of frustration were recorded serving both as a motivation for group members to become more aware of the scientific concerns and practices of their colleagues,as well as a recognition that some researchers have better skills integrating qualitative approaches than others.Nevertheless,the workshop format was an effective way to gain a common understanding of the pertinent issues that need to be addressed to meet overall multiactorapproach objectives.Working with the actor networks was identified and emphasized as a means to overcome existing barriers between academia and practice in order to coproduce a shared vision of the benefits of species mixture benefits. | Henrik HAUGGAARD-NIELSEN Søren LUND Ane K.AARE Christine A.WATSON Laurent BEDOUSSAC Jean-Noel AUBERTOT Iman R.CHONGTHAM Natalia BELLOSTAS Cairistiona F.E.TOPP Pierre HOHMANN Erik S.JENSEN Maureen STADEL Bertrand PINEL Eric JUSTES | 2021 | Frontiers of Agricultural Science and Engineering2021，8，3： | 0 |
| 2 | Machine learning-based decision tool for selecting patients with idiopathic acute pancreatitis for endosonography to exclude a biliary aetiology显示文摘BACKGROUND Biliary microlithiasis/sludge is detected in approximately 30%of patients with idiopathic acute pancreatitis(IAP).As recurrent biliary pancreatitis can be prevented,the underlying aetiology of IAP should be established.AIM To develop a machine learning(ML)based decision tool for the use of endosonography(EUS)in pancreatitis patients to detect sludge and microlithiasis.METHODS We retrospectively used routinely recorded clinical and laboratory parameters of 218 consecutive patients with confirmed AP admitted to our tertiary care hospital between 2015 and 2020.Patients who did not receive EUS as part of the diagnostic work-up and whose pancreatitis episode could be adequately explained by other causes than biliary sludge and microlithiasis were excluded.We trained supervised ML classifiers using H_(2)O.ai automatically selecting the best suitable predictor model to predict microlithiasis/sludge.The predictor model was further validated in two independent retrospective cohorts from two tertiary care centers(117 patients).RESULTS Twenty-eight categorized patients’variables recorded at admission were identified to compute the predictor model with an accuracy of 0.84[95%confidence interval(CI):0.791-0.9185],positive predictive value of 0.84,and negative predictive value of 0.80 in the identification cohort(218 patients).In the validation cohort,the robustness of the prediction model was confirmed with an accuracy of 0.76(95%CI:0.673-0.8347),positive predictive value of 0.76,and negative predictive value of 0.78(117 patients).CONCLUSION We present a robust and validated ML-based predictor model consisting of routinely recorded parameters at admission that can predict biliary sludge and microlithiasis as the cause of AP. | Simon Sirtl Michal Żorniak Eric Hohmann Georg Beyer Miriam Dibos Annika Wandel Veit Phillip Christoph Ammer-Herrmenau Albrecht Neesse Christian Schulz Jörg Schirra Julia Mayerle Ujjwal Mukund Mahajan | 2023 | World Journal of Gastroenterology2023，29，35： | 0 |
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