Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz最新文献

[Artificial intelligence in hospital logistics and operational processes]. [医院后勤和运营流程中的人工智能]。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-15 DOI: 10.1007/s00103-025-04094-6

Sylvia Kaczmarek, Sebastian Wibbeling

{"title":"[Artificial intelligence in hospital logistics and operational processes].","authors":"Sylvia Kaczmarek, Sebastian Wibbeling","doi":"10.1007/s00103-025-04094-6","DOIUrl":"https://doi.org/10.1007/s00103-025-04094-6","url":null,"abstract":"The implementation of artificial intelligence (AI) solutions in hospital logistics is becoming increasingly important for optimizing clinical processes. This paper examines the use of AI in hospital logistics and other operational areas of healthcare. Following an introduction to the fundamental role of AI in hospitals, the technological foundations and specific logistics processes are presented. A developed matrix systematically classifies the various AI solutions according to automation levels and functional areas.The potential of AI systems is illustrated through concrete application examples. AI-supported transport disposition for optimizing transport logistics, automatic material requisition for modular cabinets in inventory management, and automated nursing documentation using sensors and machine learning demonstrate the potential for increasing efficiency in operational processes.The analysis identifies key challenges in implementing AI systems in hospitals, including technical integration, data availability, system flexibility, and transparency requirements. Despite these limitations, it is becoming clear that AI-based solutions are gaining increasing importance, particularly for logistics and hospital operations. The results show that the successful deployment of AI systems depends significantly on the balance between technological innovation and practical applicability in everyday hospital routines. The paper thus contributes to understanding the potential and limitations of AI applications in hospital logistics and provides a systematic framework for their strategic implementation.","PeriodicalId":9562,"journal":{"name":"Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144636189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Artificial intelligence under scrutiny: requirements, quality criteria, and testing tools for medical applications]. [审查中的人工智能：医疗应用的要求、质量标准和测试工具]。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-14 DOI: 10.1007/s00103-025-04101-w

Jackie Ma, Eva Weicken, Frederik Pahde, Katharina Weitz, Sebastian Lapuschkin, Wojciech Samek, Thomas Wiegand

{"title":"[Artificial intelligence under scrutiny: requirements, quality criteria, and testing tools for medical applications].","authors":"Jackie Ma, Eva Weicken, Frederik Pahde, Katharina Weitz, Sebastian Lapuschkin, Wojciech Samek, Thomas Wiegand","doi":"10.1007/s00103-025-04101-w","DOIUrl":"https://doi.org/10.1007/s00103-025-04101-w","url":null,"abstract":"The use of artificial intelligence (AI) in medicine has great potential to improve quality and efficiency. At the same time, its use is associated with risks. In order to prevent harm, experts from research and politics are developing requirements, testing tools, and guidelines to identify and control these risks.This article first describes the requirements for AI in medicine. It then follows with a presentation of how concrete quality criteria and testing tools can be derived from those requirements. A deeper demonstration of \"explainability\" as a key criterion is presented as an example. A testing framework for the use of AI in medicine is also presented. Finally, the article provides an outlook on standardization of quality criteria.The development of AI, especially in medicine, is progressing quickly. Suitable testing procedures can help to minimize risks and strengthen trust in the technology. However, for the successful implementation of such testing procedures, continuous research efforts are necessary.","PeriodicalId":9562,"journal":{"name":"Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144636190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Erratum zu: Messung der körperlichen Fitness in der NAKO Gesundheitsstudie – Methoden, Qualitätssicherung und erste deskriptive Ergebnisse. 勘误表：在NAKO健康研究中测量身体健康-方法，质量保证和初步描述性结果。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-11 DOI: 10.1007/s00103-025-04083-9

Alexander Kluttig, Johannes Zschocke, Johannes Haerting, Axel Schmermund, Sylvia Gastell, Karen Steindorf, Florian Herbolsheimer, Andrea Hillreiner, Carmen Jochem, Sebastian Baumeister, Ole Sprengeler, Tobias Pischon, Lina Jaeschke, Karin B Michels, Lilian Krist, Halina Greiser, Gerhard Schmidt, Wolfgang Lieb, Sabina Waniek, Heiko Becher, Annika Jagodzinski, Sabine Schipf, Henry Völzke, Wolfgang Ahrens, Kathrin Günther, Stefanie Castell, Yvonne Kemmling, Nicole Legath, Klaus Berger, Thomas Keil, Julia Fricke, Matthias B Schulze, Markus Loeffler, Kerstin Wirkner, Oliver Kuß, Tamara Schikowski, Sonja Kalinowski, Andreas Stang, Rudolf Kaaks, Antje Damms Machado, Michael Hoffmeister, Barbara Weber, Claus-Werner Franzke, Sigrid Thierry, Anette Peters, Nadja Kartschmit, Rafael Mikolajczyk, Beate Fischer, Michael Leitzmann, Mirko Brandes

引用次数: 0

[Pornography in everyday life and sexual education among adolescents: survey results from 8th and 9th grade students in North Rhine-Westphalia]. [日常生活中的色情与青少年的性教育：对北莱茵-威斯特伐利亚州八年级和九年级学生的调查结果]。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-09 DOI: 10.1007/s00103-025-04073-x

Nicola Döring, Veronika Mikhailova, Matthias Biermann, Yasemin Bresemann, Alexander Daum, Tanita Kistinger, Mareike Wellner, Thomas Zenge Wesendonk

{"title":"[Pornography in everyday life and sexual education among adolescents: survey results from 8th and 9th grade students in North Rhine-Westphalia].","authors":"Nicola Döring, Veronika Mikhailova, Matthias Biermann, Yasemin Bresemann, Alexander Daum, Tanita Kistinger, Mareike Wellner, Thomas Zenge Wesendonk","doi":"10.1007/s00103-025-04073-x","DOIUrl":"https://doi.org/10.1007/s00103-025-04073-x","url":null,"abstract":"Background: In the digital age, minors' exposure to online pornography is increasing. However, current data for Germany are lacking.Research aim: The aim of this study was to examine the prevalence of unwanted and wanted pornography exposure among adolescents (research question 1, RQ1), their attitudes toward pornography (RQ2), their conceptions of what constitutes good sex (RQ3), and their subjective need for education about pornography (RQ4).Material and methods: Between 2023 and 2024, students in the 8th and 9th grades from various secondary schools in North Rhine-Westphalia were surveyed in a classroom setting using questionnaires. Complete datasets are available for N = 903 adolescents (85% aged 14-15 years; 54% male, 85% heterosexual).Results: Both unwanted (48%) and wanted (63%) exposure to pornography were widespread among the surveyed minors (RQ1). Their attitudes toward pornography were ambivalent: they described it as arousing yet harmful, as addictive yet fun (RQ2). In their conceptions of good sex, activities atypical of pornography (e.g., kissing, full-body caressing, declarations of love) played a greater role than those typical of pornography (e.g., hard thrusting, choking, anal intercourse, RQ3). The surveyed minors expressed a need for education about pornography, including its effects (58%) and its realism (55%, RQ4). Differences between boys and girls and between heavy and light pornography users are highlighted.Discussion: To ensure adolescents are not left alone with their experiences of sexually explicit media, it is advisable to address pornography as a topic in sexual education in an age-appropriate and factual manner.","PeriodicalId":9562,"journal":{"name":"Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144607452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[AI in rehabilitation-application of artificial mental models for personalized medicine]. [人工智能在康复中的应用——人工心理模型在个性化医疗中的应用]。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-04 DOI: 10.1007/s00103-025-04090-w

Sabine Janzen, Prajvi Saxena, Cicy Agnes, Wolfgang Maaß

{"title":"[AI in rehabilitation-application of artificial mental models for personalized medicine].","authors":"Sabine Janzen, Prajvi Saxena, Cicy Agnes, Wolfgang Maaß","doi":"10.1007/s00103-025-04090-w","DOIUrl":"https://doi.org/10.1007/s00103-025-04090-w","url":null,"abstract":"Artificial intelligence (AI) can support patient-centered care in prevention and rehabilitation. In Germany, almost 1.9 million patients were treated in rehabilitation hospitals in 2023, mostly due to musculoskeletal disorders. The success of rehabilitation depends on cooperation between patient, doctor, and therapist as well as active participation. However, cognitive limitations, language barriers, and psychological factors tackle decision-making and communication abilities of patients. This leads to incomplete or distorted data and impairs individualized therapy. A potential solution approach is to apply artificial mental models (AMMs) that anticipate patients' unknown mental models. These concepts are based on cognitive science theories and world models from AI. AMMs can optimize treatment decisions, correct misjudgments, and thus increase the success of rehabilitation. Particularly in knee rehabilitation, an AI agent can determine how patients perceive their recovery and enable individual adjustments. The BMFTR project FedWELL investigates the use of AMM in rehabilitation. A non-discriminatory base model was developed using data from online forums, user studies, and machine learning models. Initial results show that AI-supported models can predict individual assumptions and expectations of patients within the rehabilitation process and enable personalized therapies. This article presents the research design of the project and reports the first results of the initial survey phase.","PeriodicalId":9562,"journal":{"name":"Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144607451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Regulatory classification of AI-enabled products for medical use on the basis of the EU AI Act and MDR/IVDR]. [基于欧盟人工智能法案和MDR/IVDR对医疗用人工智能产品的监管分类]。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-04 DOI: 10.1007/s00103-025-04091-9

Steffen Luckner, Wolfgang Lauer

{"title":"[Regulatory classification of AI-enabled products for medical use on the basis of the EU AI Act and MDR/IVDR].","authors":"Steffen Luckner, Wolfgang Lauer","doi":"10.1007/s00103-025-04091-9","DOIUrl":"https://doi.org/10.1007/s00103-025-04091-9","url":null,"abstract":"The use of artificial intelligence (AI) in healthcare offers great potential but also presents regulatory challenges. The EU Artificial Intelligence Act (AIA), the Medical Device Regulation (MDR), and the Regulation on in vitro diagnostic medical devices (IVDR) establish the framework for the safe and ethical use of AI-based medical devices in Europe.When assessing the regulatory classification of AI software or products with AI components, it must be determined-based on the intended purpose defined by the manufacturer and the classification criteria of the MDR or IVDR-whether the product qualifies as a medical device. If so, all relevant regulations of the AIA apply in addition to those of the MDR/IVDR.Both the MDR/IVDR and the AIA assign products to different risk classes based on their respective risk potential, defining specific requirements accordingly. However, the classification criteria and implications differ between the regulatory frameworks. As a result, even medical devices in the lower MDR/IVDR risk category with involvement of a notified body are considered high-risk products under the AIA. It is therefore crucial to differentiate precisely between the respective regulations.The harmonization of regulatory requirements remains a challenge, particularly because classification under the AIA and MDR/IVDR is based on different criteria despite some similar terminology. Open questions persist, especially regarding lowest-risk medical devices and self-learning AI systems. Further development of regulatory guidelines is necessary to ensure the safe and efficient integration of innovative AI applications into healthcare. The German Federal Ministry of Health (BMG) and the Federal Institute for Drugs and Medical Devices (BfArM) are actively working at both national and European levels to develop pragmatic solutions.","PeriodicalId":9562,"journal":{"name":"Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144607453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[AI-based applications in medical image computing]. [基于人工智能的医学图像计算应用]。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-02 DOI: 10.1007/s00103-025-04093-7

Timo Kepp, Hristina Uzunova, Jan Ehrhardt, Heinz Handels

{"title":"[AI-based applications in medical image computing].","authors":"Timo Kepp, Hristina Uzunova, Jan Ehrhardt, Heinz Handels","doi":"10.1007/s00103-025-04093-7","DOIUrl":"https://doi.org/10.1007/s00103-025-04093-7","url":null,"abstract":"The processing of medical images plays a central role in modern diagnostics and therapy. Automated processing and analysis of medical images can efficiently accelerate clinical workflows and open new opportunities for improved patient care. However, the high variability, complexity, and varying quality of medical image data pose significant challenges. In recent years, the greatest progress in medical image analysis has been achieved through artificial intelligence (AI), particularly by using deep neural networks in the context of deep learning. These methods are successfully applied in medical image analysis, including segmentation, registration, and image synthesis.AI-based segmentation allows for the precise delineation of organs, tissues, or pathological changes. The application of AI-based image registration supports the accelerated creation of 3D planning models for complex surgeries by aligning relevant anatomical structures from different imaging modalities (e.g., CT, MRI, and PET) or time points. Generative AI methods can be used to generate additional image data for the improved training of AI models, thereby expanding the potential applications of deep learning methods in medicine. Examples from radiology, ophthalmology, dermatology, and surgery are described to illustrate their practical relevance and the potential of AI in image-based diagnostics and therapy.","PeriodicalId":9562,"journal":{"name":"Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Applications, challenges and a trustworthy use of artificial intelligence in public health]. [人工智能在公共卫生领域的应用、挑战和可靠使用]。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-02 DOI: 10.1007/s00103-025-04098-2

Joana Sarah Grah, Christopher Irrgang, Lars Schaade, Katharina Ladewig, Nils Körber

{"title":"[Applications, challenges and a trustworthy use of artificial intelligence in public health].","authors":"Joana Sarah Grah, Christopher Irrgang, Lars Schaade, Katharina Ladewig, Nils Körber","doi":"10.1007/s00103-025-04098-2","DOIUrl":"https://doi.org/10.1007/s00103-025-04098-2","url":null,"abstract":"The rapid advancements in artificial intelligence (AI) over recent years have resulted in its integration into people's everyday lives. The wide availability of diverse data within the public health sector opens up a number of fields of application for AI, ranging from infection research and the analysis of epidemiological data to the extraction of information from communication data such as social media, the development of new resilience strategies against climate change and the systematic evaluation of specialist literature.The quality of the underlying data is paramount to the successful implementation of AI applications. In public health research, on the one hand, there is a wide variability of data types including, but not limited to, image data, numerical data and survey data. On the other hand, availability can be limited, for example when a rare pathology is being investigated and/or stringent data protection requirements apply. Concurrently, it is imperative to maintain high ethical standards and to mitigate biases, imbalances and lack of transparency as early as possible.We delineate an approach towards the responsible and trustworthy utilisation of AI applications in public health, which leads from the initial question to the data and the model development to evaluation and emphasises the importance of careful and complete documentation.","PeriodicalId":9562,"journal":{"name":"Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Participation and co-creation in implementation research]. [实施研究中的参与与共同创造]。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-01 Epub Date: 2025-06-19 DOI: 10.1007/s00103-025-04085-7

Anja Zscheppang, Christiane Falge, Silke Betscher, Anna Köster-Eiserfunke, Jonas Fiedler, Claudia Czernik, Claudia Hoevener, Anna Kuehne

{"title":"[Participation and co-creation in implementation research].","authors":"Anja Zscheppang, Christiane Falge, Silke Betscher, Anna Köster-Eiserfunke, Jonas Fiedler, Claudia Czernik, Claudia Hoevener, Anna Kuehne","doi":"10.1007/s00103-025-04085-7","DOIUrl":"10.1007/s00103-025-04085-7","url":null,"abstract":"The aim of implementation research is to transfer evidence-based interventions from research into practice. Successful transfer requires acceptance of the interventions by users and implementers. Research processes are increasingly focussing on participatory approaches in which various stakeholders are involved in research and implementation, thereby increasing the acceptability of interventions. Depending on the intervention, participation may draw from users, research, care providers or policy and funding bodies. Citizens and patients play a crucial role in participatory processes. Participatory implementation research is a collaborative approach that combines implementation research with the co-creation of knowledge by systematically involving participants in the research process and beyond. In this way, user-centred, tailor-made, lifeworld-oriented interventions in health promotion and healthcare can be scientifically developed under real-life conditions and permanently transferred into real-world practice. This review article examines the status of participatory implementation research in Germany and outlines the concepts and framework of participatory implementation research. To this end, projects from the fields of patient care, health promotion and the community setting are described. Two examples of the long-term participation of citizens of a neighbourhood in research conducted in the urban district laboratories in Bochum and Hamburg show how continuous participation and co-creation in implementation research for prevention, health promotion and health care can succeed.An English full-text version of this article is available at SpingerLink as Supplementary Information.","PeriodicalId":9562,"journal":{"name":"Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz","volume":" ","pages":"728-737"},"PeriodicalIF":1.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12254173/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144324585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Änderung des Leitwertes für die körpergewichtsnormierte tägliche Urinausscheidung von Erwachsenen : Mitteilung der Kommission Human-Biomonitoring des Umweltbundesamtes. 成人体重标准每日排尿指南的变化：联邦环境署人类生物监测委员会的通讯。

IF 1.7 4区医学

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz Pub Date : 2025-07-01 DOI: 10.1007/s00103-025-04062-0

引用次数: 0