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您的检索式：作者名="Peter Zander"
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| 1 | The Digital Agricultural Knowledge and Information System(DAKIS):Employing digitalisation to encourage diversified and multifunctional agricultural systems显示文摘Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem services.The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems.We present the Digital Agricultural Knowledge and Information System(DAKIS)to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture.To develop the DAKIS,we specified,together with stakeholders,requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools.The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity,the capacity to foster communication and cooperation between farmers and other actors,and the ability to link multiple spatiotemporal scales and sustainability levels.To overcome these challenges,the DAKIS provides a digital platform to support farmers'decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources.The approach integrates remote and in situ sensors,artificial intelligence,modelling,stakeholder-stated demand for biodiversity and ecosystem services,and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design,including natural and agronomic factors,economic and policy considerations,and socio-cultural preferences and settings.Ultimately,the DAKIS embeds the consideration of ecosystem services,biodiversity,and sustainability into farmers'decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers'objectives and societal demands. | Ioanna Mouratiadou Nahleen Lemke Cheng Chen Ariani Wartenberg Ralf Bloch Marco Donat Thomas Gaiser Deepak Hanike Basavegowda Katharina Helming Seyed Ali Hosseini Yekani Marcos Krull Kai Lingemann Joseph Macpherson Marvin Melzer Claas Nendel Annette Piorr Mostafa Shaaban Peter Zander Cornelia Weltzien Sonoko Dorothea Bellingrath-Kimura | 2023 | Environmental Science and Ecotechnology2023，，4： | 0 |
| 2 | Artificial intelligence for characterization of diminutive colorectal polyps:A feasibility study comparing two computer-aided diagnosis systems显示文摘BACKGROUND Artificial intelligence(AI)has potential in the optical diagnosis of colorectal polyps.AIM To evaluate the feasibility of the real-time use of the computer-aided diagnosis system(CADx)AI for ColoRectal Polyps(AI4CRP)for the optical diagnosis of diminutive colorectal polyps and to compare the performance with CAD EYE^(TM)(Fujifilm,Tokyo,Japan).CADx influence on the optical diagnosis of an expert endoscopist was also investigated.METHODS AI4CRP was developed in-house and CAD EYE was proprietary software provided by Fujifilm.Both CADxsystems exploit convolutional neural networks.Colorectal polyps were characterized as benign or premalignant and histopathology was used as gold standard.AI4CRP provided an objective assessment of its characterization by presenting a calibrated confidence characterization value(range 0.0-1.0).A predefined cut-off value of 0.6 was set with values<0.6 indicating benign and values≥0.6 indicating premalignant colorectal polyps.Low confidence characterizations were defined as values 40%around the cut-off value of 0.6(<0.36 and>0.76).Self-critical AI4CRP’s diagnostic performances excluded low confidence characterizations.RESULTS AI4CRP use was feasible and performed on 30 patients with 51 colorectal polyps.Self-critical AI4CRP,excluding 14 low confidence characterizations[27.5%(14/51)],had a diagnostic accuracy of 89.2%,sensitivity of 89.7%,and specificity of 87.5%,which was higher compared to AI4CRP.CAD EYE had a 83.7%diagnostic accuracy,74.2%sensitivity,and 100.0%specificity.Diagnostic performances of the endoscopist alone(before AI)increased nonsignificantly after reviewing the CADx characterizations of both AI4CRP and CAD EYE(AI-assisted endoscopist).Diagnostic performances of the AI-assisted endoscopist were higher compared to both CADx-systems,except for specificity for which CAD EYE performed best.CONCLUSION Real-time use of AI4CRP was feasible.Objective confidence values provided by a CADx is novel and self-critical AI4CRP showed higher diagnostic performances compared to AI4CRP. | Quirine Eunice Wennie van der Zander Ramon M Schreuder Ayla Thijssen Carolus H J Kusters Nikoo Dehghani Thom Scheeve Bjorn Winkens Mirjam C M van der Ende-van Loon Peter H N de With Fons van der Sommen Ad A M Masclee Erik J Schoon | 2024 | Artificial Intelligence in Gastrointestinal Endoscopy2024，5，1： | 0 |
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