日期 影响因子
日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:
–

Preventing postoperative pulmonary complications by establishing a machine-learning assisted approach (PEPPERMINT): Study protocol for the creation of a risk prediction model

利用机器学习辅助方法预防术后肺部并发症（PEPPERMINT）：风险预测模型创建研究方案

期刊:PLoS One
影响因子:2.6
doi:10.1371/journal.pone.0329076
Trautwein, Britta; Beer, Meinrad; Blobner, Manfred; Jungwirth, Bettina; Kagerbauer, Simone Maria; Götz, Michael
PERM
发表日期：2025
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Implementation of a software-based decision support tool for guideline-appropriate preoperative evaluation: a prospective agreement study

实施基于软件的决策支持工具以进行符合指南的术前评估：一项前瞻性一致性研究

期刊:British Journal of Anaesthesia
影响因子:9.2
doi:10.1016/j.bja.2024.06.001
Kagerbauer, Simone M; Wißler, Jennifer; Andonov, Dimislav I; Ulm, Bernhard; Schneider, Gerhard; Podtschaske, Armin H; Blobner, Manfred; Jungwirth, Bettina
发表日期：2024
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Susceptibility of AutoML mortality prediction algorithms to model drift caused by the COVID pandemic

AutoML死亡率预测算法易受COVID-19疫情引起的模型漂移的影响

期刊:BMC Medical Informatics and Decision Making
影响因子:3.8
doi:10.1186/s12911-024-02428-z
Kagerbauer, Simone Maria; Ulm, Bernhard; Podtschaske, Armin Horst; Andonov, Dimislav Ivanov; Blobner, Manfred; Jungwirth, Bettina; Graessner, Martin
发表日期：2024
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Correction: Susceptibility of AutoML mortality prediction algorithms to model drift caused by the COVID pandemic

更正：AutoML死亡率预测算法易受新冠疫情引起的模型漂移影响

期刊:BMC Medical Informatics and Decision Making
影响因子:3.8
doi:10.1186/s12911-024-02454-x
Kagerbauer, Simone Maria; Ulm, Bernhard; Podtschaske, Armin Horst; Andonov, Dimislav Ivanov; Blobner, Manfred; Jungwirth, Bettina; Graessner, Martin
微生物学
新冠
发表日期：2024
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Anaesthesiologists' guideline adherence in pre-operative evaluation: a retrospective observational study

麻醉医师术前评估中指南遵循情况：一项回顾性观察研究

期刊:
影响因子:
doi:10.1186/s13741-024-00424-5
Kagerbauer, Simone Maria; Wißler, Jennifer; Blobner, Manfred; Biegert, Ferdinand; Andonov, Dimislav Ivanov; Schneider, Gerhard; Podtschaske, Armin Horst; Ulm, Bernhard; Jungwirth, Bettina
发表日期：2024
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Enabling personalized perioperative risk prediction by using a machine-learning model based on preoperative data

利用基于术前数据的机器学习模型，实现个性化的围手术期风险预测

期刊:Scientific Reports
影响因子:3.9
doi:10.1038/s41598-023-33981-8
Graeßner, Martin; Jungwirth, Bettina; Frank, Elke; Schaller, Stefan Josef; Kochs, Eberhard; Ulm, Kurt; Blobner, Manfred; Ulm, Bernhard; Podtschaske, Armin Horst; Kagerbauer, Simone Maria
发表日期：2023
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Impact of the Covid-19 pandemic on the performance of machine learning algorithms for predicting perioperative mortality

新冠疫情对机器学习算法预测围手术期死亡率性能的影响

期刊:BMC Medical Informatics and Decision Making
影响因子:3.8
doi:10.1186/s12911-023-02151-1
Andonov, D I; Ulm, B; Graessner, M; Podtschaske, A; Blobner, M; Jungwirth, B; Kagerbauer, S M
微生物学
新冠
发表日期：2023
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Wearable in-ear pulse oximetry validly measures oxygen saturation between 70% and 100%: A prospective agreement study

可穿戴式耳内脉搏血氧仪能够有效测量70%至100%之间的氧饱和度：一项前瞻性一致性研究

期刊:DIGITAL HEALTH
影响因子:3.3
doi:10.1177/20552076231211169
Bubb, Catherina Ab; Weber, Michael; Kretsch, Nadine; Heim, Ralph; Zellhuber, Incinur; Schmid, Sebastian; Kagerbauer, Simone M; Kreuzer, Johannes; Schaller, Stefan J; Blobner, Manfred; Jungwirth, Bettina
发表日期：2023
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Experiences of medical students and nursing trainees from unexpected death through simulation training

通过模拟训练，了解医学生和护理实习生在意外死亡中的经历

期刊:BMC Medical Education
影响因子:3.2
doi:10.1186/s12909-023-04638-x
Hinzmann, Dominik; Wijnen-Meijer, Marjo; Corazza, Laura; Becker, Veronika; Kagerbauer, Simone; Haseneder, Rainer; Berberat, Pascal O; Jedlicska, Nana
发表日期：2023
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Mobilisation of critically ill patients receiving norepinephrine: a retrospective cohort study

接受去甲肾上腺素治疗的危重患者的活动能力：一项回顾性队列研究

期刊:Critical Care
影响因子:9.3
doi:10.1186/s13054-022-04245-0
Lindholz, Maximilian; Schellenberg, Clara M; Grunow, Julius J; Kagerbauer, Simone; Milnik, Annette; Zickler, Daniel; Angermair, Stefan; Reißhauer, Anett; Witzenrath, Martin; Menk, Mario; Boie, Sebastian; Balzer, Felix; Schaller, Stefan J
免疫/内分泌
发表日期：2022
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