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  1. Buch ; Dissertation / Habilitation: Biomarker in der Intensivmedizin

    Kunze, Julian

    diagnostischer und prognostischer Wert von ADMA und SDMA bei kritisch kranken Patienten

    2016  

    Verfasserangabe vorgelegt von Julian Benedict Kunze
    Sprache Deutsch
    Umfang 70 Seiten, Illustrationen, Diagramme
    Erscheinungsort Aachen
    Erscheinungsland Deutschland
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2016
    Anmerkung Deutsche und englische Zusammenfassung
    HBZ-ID HT019071349
    Datenquelle Katalog ZB MED Medizin, Gesundheit

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    Verfügbar in ZB MED Köln/Königswinter

    SignaturLeihstatusStandort
    2017 D 318 bestellbar zur Ausleihe Magazin

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  2. Buch ; Online: Non-Holonomic RRT & MPC

    Bojadžić, Damir / Kunze, Julian / Osmanković, Dinko / Malmir, Mohammadhossein / Knoll, Alois

    Path and Trajectory Planning for an Autonomous Cycle Rickshaw

    2021  

    Abstract: This paper presents a novel hierarchical motion planning approach based on Rapidly-Exploring Random Trees (RRT) for global planning and Model Predictive Control (MPC) for local planning. The approach targets a three-wheeled cycle rickshaw (trishaw) used ... ...

    Abstract This paper presents a novel hierarchical motion planning approach based on Rapidly-Exploring Random Trees (RRT) for global planning and Model Predictive Control (MPC) for local planning. The approach targets a three-wheeled cycle rickshaw (trishaw) used for autonomous urban transportation in shared spaces. Due to the nature of the vehicle, the algorithms had to be adapted in order to adhere to non-holonomic kinematic constraints using the Kinematic Single-Track Model. The vehicle is designed to offer transportation for people and goods in shared environments such as roads, sidewalks, bicycle lanes but also open spaces that are often occupied by other traffic participants. Therefore, the algorithm presented in this paper needs to anticipate and avoid dynamic obstacles, such as pedestrians or bicycles, but also be fast enough in order to work in real-time so that it can adapt to changes in the environment. Our approach uses an RRT variant for global planning that has been modified for single-track kinematics and improved by exploiting dead-end nodes. This allows us to compute global paths in unstructured environments very fast. In a second step, our MPC-based local planner makes use of the global path to compute the vehicle's trajectory while incorporating dynamic obstacles such as pedestrians and other road users. Our approach has shown to work both in simulation as well as first real-life tests and can be easily extended for more sophisticated behaviors.

    Comment: Submitted to IROS 2021, 6 pages, 4 figures
    Schlagwörter Computer Science - Robotics
    Thema/Rubrik (Code) 629
    Erscheinungsdatum 2021-03-10
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel ; Online: Future Mobile Device Usage, Requirements, and Expectations of Physicians in German University Hospitals: Web-Based Survey.

    Maassen, Oliver / Fritsch, Sebastian / Gantner, Julia / Deffge, Saskia / Kunze, Julian / Marx, Gernot / Bickenbach, Johannes

    Journal of medical Internet research

    2020  Band 22, Heft 12, Seite(n) e23955

    Abstract: Background: The use of mobile devices in hospital care constantly increases. However, smartphones and tablets have not yet widely become official working equipment in medical care. Meanwhile, the parallel use of private and official devices in hospitals ...

    Abstract Background: The use of mobile devices in hospital care constantly increases. However, smartphones and tablets have not yet widely become official working equipment in medical care. Meanwhile, the parallel use of private and official devices in hospitals is common. Medical staff use smartphones and tablets in a growing number of ways. This mixture of devices and how they can be used is a challenge to persons in charge of defining strategies and rules for the usage of mobile devices in hospital care.
    Objective: Therefore, we aimed to examine the status quo of physicians' mobile device usage and concrete requirements and their future expectations of how mobile devices can be used.
    Methods: We performed a web-based survey among physicians in 8 German university hospitals from June to October 2019. The online survey was forwarded by hospital management personnel to physicians from all departments involved in patient care at the local sites.
    Results: A total of 303 physicians from almost all medical fields and work experience levels completed the web-based survey. The majority regarded a tablet (211/303, 69.6%) and a smartphone (177/303, 58.4%) as the ideal devices for their operational area. In practice, physicians are still predominantly using desktop computers during their worktime (mean percentage of worktime spent on a desktop computer: 56.8%; smartphone: 12.8%; tablet: 3.6%). Today, physicians use mobile devices for basic tasks such as oral (171/303, 56.4%) and written (118/303, 38.9%) communication and to look up dosages, diagnoses, and guidelines (194/303, 64.0%). Respondents are also willing to use mobile devices for more advanced applications such as an early warning system (224/303, 73.9%) and mobile electronic health records (211/303, 69.6%). We found a significant association between the technical affinity and the preference of device in medical care (χs2=53.84, P<.001) showing that with increasing self-reported technical affinity, the preference for smartphones and tablets increases compared to desktop computers.
    Conclusions: Physicians in German university hospitals have a high technical affinity and positive attitude toward the widespread implementation of mobile devices in clinical care. They are willing to use official mobile devices in clinical practice for basic and advanced mobile health uses. Thus, the reason for the low usage is not a lack of willingness of the potential users. Challenges that hinder the wider adoption of mobile devices might be regulatory, financial and organizational issues, and missing interoperability standards of clinical information systems, but also a shortage of areas of application in which workflows are adapted for (small) mobile devices.
    Mesh-Begriff(e) Computers, Handheld/standards ; Germany ; Hospitals, University ; Humans ; Internet/standards ; Mobile Applications/statistics & numerical data ; Physicians/standards ; Surveys and Questionnaires
    Sprache Englisch
    Erscheinungsdatum 2020-12-21
    Erscheinungsland Canada
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2028830-X
    ISSN 1438-8871 ; 1439-4456
    ISSN (online) 1438-8871
    ISSN 1439-4456
    DOI 10.2196/23955
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel ; Online: Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals: Web-Based Survey.

    Maassen, Oliver / Fritsch, Sebastian / Palm, Julia / Deffge, Saskia / Kunze, Julian / Marx, Gernot / Riedel, Morris / Schuppert, Andreas / Bickenbach, Johannes

    Journal of medical Internet research

    2021  Band 23, Heft 3, Seite(n) e26646

    Abstract: Background: The increasing development of artificial intelligence (AI) systems in medicine driven by researchers and entrepreneurs goes along with enormous expectations for medical care advancement. AI might change the clinical practice of physicians ... ...

    Abstract Background: The increasing development of artificial intelligence (AI) systems in medicine driven by researchers and entrepreneurs goes along with enormous expectations for medical care advancement. AI might change the clinical practice of physicians from almost all medical disciplines and in most areas of health care. While expectations for AI in medicine are high, practical implementations of AI for clinical practice are still scarce in Germany. Moreover, physicians' requirements and expectations of AI in medicine and their opinion on the usage of anonymized patient data for clinical and biomedical research have not been investigated widely in German university hospitals.
    Objective: This study aimed to evaluate physicians' requirements and expectations of AI in medicine and their opinion on the secondary usage of patient data for (bio)medical research (eg, for the development of machine learning algorithms) in university hospitals in Germany.
    Methods: A web-based survey was conducted addressing physicians of all medical disciplines in 8 German university hospitals. Answers were given using Likert scales and general demographic responses. Physicians were asked to participate locally via email in the respective hospitals.
    Results: The online survey was completed by 303 physicians (female: 121/303, 39.9%; male: 173/303, 57.1%; no response: 9/303, 3.0%) from a wide range of medical disciplines and work experience levels. Most respondents either had a positive (130/303, 42.9%) or a very positive attitude (82/303, 27.1%) towards AI in medicine. There was a significant association between the personal rating of AI in medicine and the self-reported technical affinity level (H
    Conclusions: Physicians in stationary patient care in German university hospitals show a generally positive attitude towards using most AI applications in medicine. Along with this optimism comes several expectations and hopes that AI will assist physicians in clinical decision making. Especially in fields of medicine where huge amounts of data are processed (eg, imaging procedures in radiology and pathology) or data are collected continuously (eg, cardiology and intensive care medicine), physicians' expectations of AI to substantially improve future patient care are high. In the study, the greatest potential was seen in the application of AI for the identification of drug interactions, assumedly due to the rising complexity of drug administration to polymorbid, polypharmacy patients. However, for the practical usage of AI in health care, regulatory and organizational challenges still have to be mastered.
    Mesh-Begriff(e) Artificial Intelligence ; Female ; Hospitals, University ; Humans ; Internet ; Male ; Motivation ; Physicians ; Radiology ; Surveys and Questionnaires
    Sprache Englisch
    Erscheinungsdatum 2021-03-05
    Erscheinungsland Canada
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2028830-X
    ISSN 1438-8871 ; 1438-8871
    ISSN (online) 1438-8871
    ISSN 1438-8871
    DOI 10.2196/26646
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Artikel: Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients.

    Fritsch, Sebastian J / Blankenheim, Andrea / Wahl, Alina / Hetfeld, Petra / Maassen, Oliver / Deffge, Saskia / Kunze, Julian / Rossaint, Rolf / Riedel, Morris / Marx, Gernot / Bickenbach, Johannes

    Digital health

    2022  Band 8, Seite(n) 20552076221116772

    Abstract: Objective: The attitudes about the usage of artificial intelligence in healthcare are controversial. Unlike the perception of healthcare professionals, the attitudes of patients and their companions have been of less interest so far. In this study, we ... ...

    Abstract Objective: The attitudes about the usage of artificial intelligence in healthcare are controversial. Unlike the perception of healthcare professionals, the attitudes of patients and their companions have been of less interest so far. In this study, we aimed to investigate the perception of artificial intelligence in healthcare among this highly relevant group along with the influence of digital affinity and sociodemographic factors.
    Methods: We conducted a cross-sectional study using a paper-based questionnaire with patients and their companions at a German tertiary referral hospital from December 2019 to February 2020. The questionnaire consisted of three sections examining (a) the respondents' technical affinity, (b) their perception of different aspects of artificial intelligence in healthcare and (c) sociodemographic characteristics.
    Results: From a total of 452 participants, more than 90% already read or heard about artificial intelligence, but only 24% reported good or expert knowledge. Asked on their general perception, 53.18% of the respondents rated the use of artificial intelligence in medicine as positive or very positive, but only 4.77% negative or very negative. The respondents denied concerns about artificial intelligence, but strongly agreed that artificial intelligence must be controlled by a physician. Older patients, women, persons with lower education and technical affinity were more cautious on the healthcare-related artificial intelligence usage.
    Conclusions: German patients and their companions are open towards the usage of artificial intelligence in healthcare. Although showing only a mediocre knowledge about artificial intelligence, a majority rated artificial intelligence in healthcare as positive. Particularly, patients insist that a physician supervises the artificial intelligence and keeps ultimate responsibility for diagnosis and therapy.
    Sprache Englisch
    Erscheinungsdatum 2022-08-08
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 2819396-9
    ISSN 2055-2076
    ISSN 2055-2076
    DOI 10.1177/20552076221116772
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel ; Online: Future Mobile Device Usage, Requirements, and Expectations of Physicians in German University Hospitals

    Maassen, Oliver / Fritsch, Sebastian / Gantner, Julia / Deffge, Saskia / Kunze, Julian / Marx, Gernot / Bickenbach, Johannes

    Journal of Medical Internet Research, Vol 22, Iss 12, p e

    Web-Based Survey

    2020  Band 23955

    Abstract: BackgroundThe use of mobile devices in hospital care constantly increases. However, smartphones and tablets have not yet widely become official working equipment in medical care. Meanwhile, the parallel use of private and official devices in hospitals is ...

    Abstract BackgroundThe use of mobile devices in hospital care constantly increases. However, smartphones and tablets have not yet widely become official working equipment in medical care. Meanwhile, the parallel use of private and official devices in hospitals is common. Medical staff use smartphones and tablets in a growing number of ways. This mixture of devices and how they can be used is a challenge to persons in charge of defining strategies and rules for the usage of mobile devices in hospital care. ObjectiveTherefore, we aimed to examine the status quo of physicians’ mobile device usage and concrete requirements and their future expectations of how mobile devices can be used. MethodsWe performed a web-based survey among physicians in 8 German university hospitals from June to October 2019. The online survey was forwarded by hospital management personnel to physicians from all departments involved in patient care at the local sites. ResultsA total of 303 physicians from almost all medical fields and work experience levels completed the web-based survey. The majority regarded a tablet (211/303, 69.6%) and a smartphone (177/303, 58.4%) as the ideal devices for their operational area. In practice, physicians are still predominantly using desktop computers during their worktime (mean percentage of worktime spent on a desktop computer: 56.8%; smartphone: 12.8%; tablet: 3.6%). Today, physicians use mobile devices for basic tasks such as oral (171/303, 56.4%) and written (118/303, 38.9%) communication and to look up dosages, diagnoses, and guidelines (194/303, 64.0%). Respondents are also willing to use mobile devices for more advanced applications such as an early warning system (224/303, 73.9%) and mobile electronic health records (211/303, 69.6%). We found a significant association between the technical affinity and the preference of device in medical care (χs2=53.84, P<.001) showing that with increasing self-reported technical affinity, the preference for smartphones and tablets increases compared to desktop ...
    Schlagwörter Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
    Thema/Rubrik (Code) 600
    Sprache Englisch
    Erscheinungsdatum 2020-12-01T00:00:00Z
    Verlag JMIR Publications
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel ; Online: Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals

    Maassen, Oliver / Fritsch, Sebastian / Palm, Julia / Deffge, Saskia / Kunze, Julian / Marx, Gernot / Riedel, Morris / Schuppert, Andreas / Bickenbach, Johannes

    Journal of Medical Internet Research, Vol 23, Iss 3, p e

    Web-Based Survey

    2021  Band 26646

    Abstract: BackgroundThe increasing development of artificial intelligence (AI) systems in medicine driven by researchers and entrepreneurs goes along with enormous expectations for medical care advancement. AI might change the clinical practice of physicians from ... ...

    Abstract BackgroundThe increasing development of artificial intelligence (AI) systems in medicine driven by researchers and entrepreneurs goes along with enormous expectations for medical care advancement. AI might change the clinical practice of physicians from almost all medical disciplines and in most areas of health care. While expectations for AI in medicine are high, practical implementations of AI for clinical practice are still scarce in Germany. Moreover, physicians’ requirements and expectations of AI in medicine and their opinion on the usage of anonymized patient data for clinical and biomedical research have not been investigated widely in German university hospitals. ObjectiveThis study aimed to evaluate physicians’ requirements and expectations of AI in medicine and their opinion on the secondary usage of patient data for (bio)medical research (eg, for the development of machine learning algorithms) in university hospitals in Germany. MethodsA web-based survey was conducted addressing physicians of all medical disciplines in 8 German university hospitals. Answers were given using Likert scales and general demographic responses. Physicians were asked to participate locally via email in the respective hospitals. ResultsThe online survey was completed by 303 physicians (female: 121/303, 39.9%; male: 173/303, 57.1%; no response: 9/303, 3.0%) from a wide range of medical disciplines and work experience levels. Most respondents either had a positive (130/303, 42.9%) or a very positive attitude (82/303, 27.1%) towards AI in medicine. There was a significant association between the personal rating of AI in medicine and the self-reported technical affinity level (H4=48.3, P<.001). A vast majority of physicians expected the future of medicine to be a mix of human and artificial intelligence (273/303, 90.1%) but also requested a scientific evaluation before the routine implementation of AI-based systems (276/303, 91.1%). Physicians were most optimistic that AI applications would identify drug interactions (280/303, 92.4%) to improve patient care substantially but were quite reserved regarding AI-supported diagnosis of psychiatric diseases (62/303, 20.5%). Of the respondents, 82.5% (250/303) agreed that there should be open access to anonymized patient databases for medical and biomedical research. ConclusionsPhysicians in stationary patient care in German university hospitals show a generally positive attitude towards using most AI applications in medicine. Along with this optimism comes several expectations and hopes that AI will assist physicians in clinical decision making. Especially in fields of medicine where huge amounts of data are processed (eg, imaging procedures in radiology and pathology) or data are collected continuously (eg, cardiology and intensive care medicine), physicians’ expectations of AI to substantially improve future patient care are high. In the study, the greatest potential was seen in the application of AI for the identification of drug interactions, assumedly due to the rising complexity of drug administration to polymorbid, polypharmacy patients. However, for the practical usage of AI in health care, regulatory and organizational challenges still have to be mastered.
    Schlagwörter Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
    Thema/Rubrik (Code) 310
    Sprache Englisch
    Erscheinungsdatum 2021-03-01T00:00:00Z
    Verlag JMIR Publications
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  8. Konferenzbeitrag ; Online: UAV-borne remote sensing for AI-assisted support of search and rescue missions

    Herschel, Reinhold / Wallrath, Patrick / Hofstätter, Michael / Taupe, Philip / Krüger, Emily / Philippi, Martina / Kunze, Julian / Rotter, Jan Michel / Heusinger-Heß, Victoria / Ari, Meral / Kastner, René / Al-Akrawi, Astrid

    2022  

    Abstract: In search and rescue (SAR) missions every minute counts. Semi-collapsed buildings are among the difficult scenarios encountered by search and rescue teams. An UAV-based exploration system can provide crucial information on the accessibility of different ... ...

    Abstract In search and rescue (SAR) missions every minute counts. Semi-collapsed buildings are among the difficult scenarios encountered by search and rescue teams. An UAV-based exploration system can provide crucial information on the accessibility of different sectors, hazards, and injured people. The research project “UAV-Rescue” aims to provide UAV-borne sensing and investigate the use of AI to support this powerful tool. The sensor suite contains a radar sensor for detecting people based on breath and pulse movement. A neural network interprets the extracted data to identify signs of human life and as such persons that need rescuing. We also fuse radar and lidar data to explore the environment of the UAV and obtain a robust basis for simultaneous localization and mapping even under restricted visibility conditions. Additionally, we plan to use AI to support the path planning of the drone taking the digital map as input. Furthermore, AI is leveraged to map intact and damaged building structures. Potentially hazardous gases common to urban settings are tracked. We fuse the acquired information into a model of the explored area with marked locations of potential hazards and people to be rescued. The project also addresses ethical and societal issues raised by the use of UAVs close to people as well as AI supported decision making. The talk will present the system concept including interfaces and sensor fusion approaches. We will show first results of a research project from static and dynamic measurement campaigns demonstrating the capability of radar and lidar based sensing in a complex urban environment.
    Thema/Rubrik (Code) 910
    Sprache Englisch
    Erscheinungsland de
    Dokumenttyp Konferenzbeitrag ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  9. Artikel: big data und smartphones auf der intensivstation. Wie Smartphone und Künstliche Intelligenz dabei helfen, beatmete Patienten zu behandeln

    Marx, Gernot / Fritsch, Sebastian / Bickenbach, Johannes / Kunze, Julian / Maaßen, Oliver / Deffge, Saskia / Haferkamp, Silke / Schuppert, Andreas

    gesundhyte.de

    2020  Band -, Heft 13, Seite(n) 30

    Sprache Deutsch
    Dokumenttyp Artikel
    ZDB-ID 3044168-7
    ISSN 2702-2544
    Datenquelle Current Contents Medizin

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  10. Artikel ; Online: Regulation and prognostic relevance of symmetric dimethylarginine serum concentrations in critical illness and sepsis.

    Koch, Alexander / Weiskirchen, Ralf / Bruensing, Jan / Dückers, Hanna / Buendgens, Lukas / Kunze, Julian / Matthes, Michael / Luedde, Tom / Trautwein, Christian / Tacke, Frank

    Mediators of inflammation

    2013  Band 2013, Seite(n) 413826

    Abstract: In systemic inflammation and sepsis, endothelial activation and microvascular dysfunction are characteristic features that promote multiorgan failure. As symmetric dimethylarginine (SDMA) impacts vascular tension and integrity via modulating nitric oxide ...

    Abstract In systemic inflammation and sepsis, endothelial activation and microvascular dysfunction are characteristic features that promote multiorgan failure. As symmetric dimethylarginine (SDMA) impacts vascular tension and integrity via modulating nitric oxide (NO) pathways, we investigated circulating SDMA in critical illness and sepsis. 247 critically ill patients (160 with sepsis, 87 without sepsis) were studied prospectively upon admission to the medical intensive care unit (ICU) and on day 7, in comparison to 84 healthy controls. SDMA serum levels were significantly elevated in critically ill patients at admission to ICU compared to controls and remained stably elevated during the first week of ICU treatment. The highest SDMA levels were found in patients with sepsis. SDMA levels closely correlated with disease severity scores, biomarkers of inflammation, and organ failure (renal, hepatic, and circulatory). We identified SDMA serum concentrations at admission as an independent prognostic biomarker in critically ill patients not only for short-term mortality at the ICU but also for unfavourable long-term survival. Thus, the significant increase of circulating SDMA in critically ill patients indicates a potential pathogenic involvement in endothelial dysfunction during sepsis and may be useful for mortality risk stratification at the ICU.
    Mesh-Begriff(e) Adolescent ; Adult ; Aged ; Aged, 80 and over ; Arginine/analogs & derivatives ; Arginine/blood ; Biomarkers/blood ; Critical Care ; Critical Illness ; Female ; Gene Expression Regulation ; Humans ; Inflammation ; Male ; Middle Aged ; Multiple Organ Failure/pathology ; Multivariate Analysis ; Prognosis ; Regression Analysis ; Risk Factors ; Sepsis/blood ; Sepsis/diagnosis ; Young Adult
    Chemische Substanzen Biomarkers ; symmetric dimethylarginine (49787G1ULV) ; Arginine (94ZLA3W45F)
    Sprache Englisch
    Erscheinungsdatum 2013-06-27
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1137605-3
    ISSN 1466-1861 ; 0962-9351
    ISSN (online) 1466-1861
    ISSN 0962-9351
    DOI 10.1155/2013/413826
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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