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您的检索式：作者名="Adrian Jonas"
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| 1 | 针对患者利益的机器学习和人工智能研究:在透明性、可重复性、伦理和有效性等方面的20个关键问题显示文摘机器学习(ML)、人工智能(AI)和其他现代统计方法正为利用先前尚未开发且极速增长的数据资源提供新的机会,以期让患者获益。尽管目前正在进行许多有前景的研究,特别是在图像方面,但就文献整体而言还缺乏透明度、对可重复性清晰的阐述、对潜在伦理问题的探究,以及对有效性的明确验证。这些问题的存在有许多原因,其中最重要的一点(为此我们提供了初步解决方案)就是当前缺乏针对ML和AI的最佳实践指南。我们认为从事研究的跨学科团队和应用ML/AI影响健康的项目,将因解决有关透明度、可重复性、伦理和有效性(TREE)的一系列问题而受益。这里提出的20个关键问题为研究团队提供了一个研究设计、实施和报告框架;帮助编辑和同行评审专家评估文献的贡献;让患者、临床医生和政策制定者评估新发现可能会给患者带来的获益。 | Sebastian Vollmer Bilal A Mateen Gergo Bohner Franz J Kirdly Rayid Ghani Pall Jonsson Sarah Cumbers Adrian Jonas Katherine S L McAllister Puja Myles David Granger Mark Birse Richard Branson Karel G M Moons Gary S Collins John P A Chris Holmes Harry Hemingwayp 李峰(译) 徐磊(校) 赵邑(校) | 2020 | 英国医学杂志中文版2020，23，9： | 5 |
| 2 | Androgen and estrogen receptors in the human corpus cavernosum penis: immunohistochemical and cell culture results显示文摘 | Dirk Schultheiss Rafael Badalyan Adrian Pilatz Alexander I. Gabouev Norbert Schlote J?rg Wefer Reinhard Wasielewski Heike Mertsching Michael Sohn Christian G. Stief Udo Jonas | 2003 | World Journal of Urology2003，，5： | 1 |
| 3 | CODE-EHR:临床研究中运用结构化电子医疗记录的最佳实践框架显示文摘改善患者生存质量是全球临床医学的发展目标,大数据是实现其发展的关键所在。技术进步使结构化电子医疗记录得以常规化,也可能会改善缺失重要临床证据的问题。虽然大数据及其相关分析在新冠大流行期间发挥了重要作用,但也存在严重的缺陷。证实、核验、数据隐私以及对科学研究社会责任的践行是一项重要挑战。欧洲心脏病协会和BigData@Heart联盟已经收集了包括患者代表、临床医生、科研人员、监管机构、期刊编辑和企业代表在内的多元化国际参与者,提出了CODE-EHR的最低标准框架。为改进研究设计、提高信息透明度提供方法手段,同时为实现医疗保健数据的稳健并能够有效运用制定了技术路线图。 | Dipak Kotecha Folkert W Asselbergs Stephan Achenbach Stefan DAnker Dan Atars Colin Baigent Amitava Banerjee Birgit Beger Cunnar Brobert Barbara Casadei Cinzia Ceccarelli Martin R Cowie Filippo Crea Maureen Cronin Spiros Denaxas Andrea Derix Donna Fitzsimons Martin Fredriksson Chris PGale Georgios V Ckoutos Wim Goettsch Harry Hemingway Martin Ingvaris Adrian Jonas's Robert Kazmierski Susanne Logstrup R Thomas Lumbers Thomas F Lischer Paul McGreavy leana L Pina Lothar Roesiga Carl Steinbeisser Mats Sundgren Benoit Tyl Chislaine van Thiel Kees van Bochove Panos EVardas Tiago Villanueva Marilena Vrana Wim Weber Franz Weidinger Stephan Windecker Angela Wood Diederick E Grobbee 创新药物计划BigData@Heart联盟 欧洲心脏病协会 CODE-EHR国际共识小组 宋奇繁(译) 汪奕名(译) | 2022 | 英国医学杂志中文版2022，25，12： | 0 |
| 4 | Observation of a single protein by ultrafast X-ray diffraction显示文摘The idea of using ultrashort X-ray pulses to obtain images of single proteins frozen in time has fascinated and inspired many.It was one of the arguments for building X-ray free-electron lasers.According to theory,the extremely intense pulses provide sufficient signal to dispense with using crystals as an amplifier,and the ultrashort pulse duration permits capturing the diffraction data before the sample inevitably explodes.This was first demonstrated on biological samples a decade ago on the giant mimivirus.Since then,a large collaboration has been pushing the limit of the smallest sample that can be imaged.The ability to capture snapshots on the timescale of atomic vibrations,while keeping the sample at room temperature,may allow probing the entire conformational phase space of macromolecules.Here we show the first observation of an X-ray diffraction pattern from a single protein,that of Escherichia coli GroEL which at 14 nm in diameter is the smallest biological sample ever imaged by X-rays,and demonstrate that the concept of diffraction before destruction extends to single proteins.From the pattern,it is possible to determine the approximate orientation of the protein.Our experiment demonstrates the feasibility of ultrafast imaging of single proteins,opening the way to single-molecule time-resolved studies on the femtosecond timescale. | Tomas Ekeberg Dameli Assalauova Johan Bielecki Rebecca Boll Benedikt J.Daurer Lutz A.Eichacker Linda E.Franken Davide E.Galli Luca Gelisio Lars Gumprecht Laura H.Gunn Janos Hajdu Robert Hartmann Dirk Hasse Alexandr Ignatenko Jayanath Koliyadu Olena Kulyk Ruslan Kurta Markus Kuster Wolfgang Lugmayr Jannik Lübke Adrian P.Mancuso Tommaso Mazza Carl Nettelblad Yevheniy Ovcharenko Daniel E.Rivas Max Rose Amit K.Samanta Philipp Schmidt Egor Sobolev Nicusor Timneanu Sergey Usenko Daniel Westphal Tamme Wollweber Lena Worbs Paul Lourdu Xavier Hazem Yousef Kartik Ayyer Henry N.Chapman Jonas A.Sellberg Carolin Seuring Ivan A.Vartanyants Jochen Küpper Michael Meyer Filipe R.N.C.Maia | 2024 | Light(Science & Applications)2024，13，1： | 0 |
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