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  1. Article ; Online: Predictive Models for Health Deterioration: Understanding Disease Pathways for Personalized Medicine.

    Eskofier, Bjoern M / Klucken, Jochen

    Annual review of biomedical engineering

    2023  Volume 25, Page(s) 131–156

    Abstract: Artificial intelligence (AI) and machine learning (ML) methods are currently widely employed in medicine and healthcare. A PubMed search returns more than 100,000 articles on these topics published between 2018 and 2022 alone. Notwithstanding several ... ...

    Abstract Artificial intelligence (AI) and machine learning (ML) methods are currently widely employed in medicine and healthcare. A PubMed search returns more than 100,000 articles on these topics published between 2018 and 2022 alone. Notwithstanding several recent reviews in various subfields of AI and ML in medicine, we have yet to see a comprehensive review around the methods' use in longitudinal analysis and prediction of an individual patient's health status within a personalized disease pathway. This review seeks to fill that gap. After an overview of the AI and ML methods employed in this field and of specific medical applications of models of this type, the review discusses the strengths and limitations of current studies and looks ahead to future strands of research in this field. We aim to enable interested readers to gain a detailed impression of the research currently available and accordingly plan future work around predictive models for deterioration in health status.
    MeSH term(s) Humans ; Artificial Intelligence ; Precision Medicine ; Machine Learning
    Language English
    Publishing date 2023-02-28
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 1448425-0
    ISSN 1545-4274 ; 1523-9829
    ISSN (online) 1545-4274
    ISSN 1523-9829
    DOI 10.1146/annurev-bioeng-110220-030247
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  2. Book ; Thesis: Zur regulatorischen Bedeutung von Determinanten des zellulären Lipidstoffwechsels in der Differenzierung mononukleärer Phagozyten

    Klucken, Jochen

    2000  

    Author's details vorgelegt von Jochen Klucken
    Language German
    Size V, 146 S., Ill., graph. Darst., 21 cm
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Regensburg, Univ., Diss., 2000
    HBZ-ID HT013174133
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
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  3. Book ; Online ; Thesis: Evaluation einer sensorbasierten Ganganalyse bei der Komplexbehandlung des idiopathischen Parkinson Syndrom

    Jakob, Verena [Verfasser] / Klucken, Jochen [Akademischer Betreuer] / Klucken, Jochen [Gutachter]

    2022  

    Author's details Verena Jakob ; Gutachter: Jochen Klucken ; Betreuer: Jochen Klucken
    Keywords Medizin, Gesundheit ; Medicine, Health
    Subject code sg610
    Language German
    Publisher Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
    Publishing place Erlangen
    Document type Book ; Online ; Thesis
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  4. Book ; Online ; Thesis: Objective sensor-based gait measures reflect motor impairment in multiple sclerosis patients

    Flachenecker, Felix [Verfasser] / Klucken, Jochen [Akademischer Betreuer] / Klucken, Jochen [Gutachter]

    2022  

    Author's details Felix Flachenecker ; Gutachter: Jochen Klucken ; Betreuer: Jochen Klucken
    Keywords Medizin, Gesundheit ; Medicine, Health
    Subject code sg610
    Language German
    Publisher Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
    Publishing place Erlangen
    Document type Book ; Online ; Thesis
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  5. Article: Progression subtypes in Parkinson's disease identified by a data-driven multi cohort analysis.

    Hähnel, Tom / Raschka, Tamara / Sapienza, Stefano / Klucken, Jochen / Glaab, Enrico / Corvol, Jean-Christophe / Falkenburger, Björn H / Fröhlich, Holger

    NPJ Parkinson's disease

    2024  Volume 10, Issue 1, Page(s) 95

    Abstract: The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting counseling and inflating the number of patients needed to test potential neuroprotective treatments. Moreover, disease subtypes might require different therapies. ... ...

    Abstract The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting counseling and inflating the number of patients needed to test potential neuroprotective treatments. Moreover, disease subtypes might require different therapies. This work uses a data-driven approach to investigate how observed heterogeneity in PD can be explained by the existence of distinct PD progression subtypes. To derive stable PD progression subtypes in an unbiased manner, we analyzed multimodal longitudinal data from three large PD cohorts and performed extensive cross-cohort validation. A latent time joint mixed-effects model (LTJMM) was used to align patients on a common disease timescale. Progression subtypes were identified by variational deep embedding with recurrence (VaDER). In each cohort, we identified a fast-progressing and a slow-progressing subtype, reflected by different patterns of motor and non-motor symptoms progression, survival rates, treatment response, features extracted from DaTSCAN imaging and digital gait assessments, education, and Alzheimer's disease pathology. Progression subtypes could be predicted with ROC-AUC up to 0.79 for individual patients when a one-year observation period was used for model training. Simulations demonstrated that enriching clinical trials with fast-progressing patients based on these predictions can reduce the required cohort size by 43%. Our results show that heterogeneity in PD can be explained by two distinct subtypes of PD progression that are stable across cohorts. These subtypes align with the brain-first vs. body-first concept, which potentially provides a biological explanation for subtype differences. Our predictive models will enable clinical trials with significantly lower sample sizes by enriching fast-progressing patients.
    Language English
    Publishing date 2024-05-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2819218-7
    ISSN 2373-8057
    ISSN 2373-8057
    DOI 10.1038/s41531-024-00712-3
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  6. Article: Wearables als unterstützendes Tool für den Paradigmenwechsel in der Versorgung von Parkinson Patienten

    Thun-Hohenstein, Caroline / Klucken, Jochen

    Klinische Neurophysiologie

    2021  Volume 52, Issue 01, Page(s) 44–51

    Abstract: Tragbare Sensoren – „Wearables“ – eignen sich, Funktionsstörungen bei Parkinson Patienten zu erheben und werden zur Prävention, Prädiktion, Diagnostik und Therapieunterstützung genutzt. In der Forschung erhöhen sie die Reliabilität der erhobenen Daten ... ...

    Abstract Tragbare Sensoren – „Wearables“ – eignen sich, Funktionsstörungen bei Parkinson Patienten zu erheben und werden zur Prävention, Prädiktion, Diagnostik und Therapieunterstützung genutzt. In der Forschung erhöhen sie die Reliabilität der erhobenen Daten und stellen bessere Studien-Endpunkte dar, als die herkömmlichen, subjektiven und wenig quantitativen Rating- und Selbstbeurteilungsskalen. Untersucht werden motorische Symptome wie Tremor, Bradykinese und Gangstörungen und auch nicht motorische Symptome. In der Home-Monitoringanwendung kann der Ist-Zustand des Patienten im realen Leben untersucht werden, die Therapie überwacht, die Adhärenz verbessert und die Compliance überprüft werden. Zusätzlich können Wearables interventionell zur Verbesserung von Symptomen eingesetzt werden wie z. B. Cueing, Gamification oder Coaching. Der Transfer von Laborbedingungen in den häuslichen Alltag ist eine medizinisch-technische Herausforderung. Optimierte Versorgungsmodelle müssen entwickelt werden und der tatsächliche Nutzen für den individuellen Patienten in weiteren Studien belegt werden.
    Keywords Morbus Parkinson ; Wearable ; Ganganalyse ; Value-based-medicine ; Versorgungseffekt ; Parkinson’s disease ; wearables ; gait analysis ; value-based medicine ; care effect
    Language German
    Publishing date 2021-02-23
    Publisher Georg Thieme Verlag KG
    Publishing place Stuttgart ; New York
    Document type Article
    ZDB-ID 80107-0
    ISSN 1439-4081 ; 1434-0275 ; 0012-7590
    ISSN (online) 1439-4081
    ISSN 1434-0275 ; 0012-7590
    DOI 10.1055/a-1353-9413
    Database Thieme publisher's database

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  7. Book ; Online ; Thesis: Biochemische Charakterisierung eines neuen Synucleinopathie-Mausmodells und die Auswirkungen einer Laufbandintervention auf die Expression von alpha-Synuclein

    Bode, Frederik Olaf [Verfasser] / Klucken, Jochen Akademischer Betreuer] / Klucken, Jochen [Gutachter] / [Blümcke, Ingmar [Gutachter]

    2022  

    Author's details Frederik Olaf Bode ; Gutachter: Jochen Klucken, Ingmar Blümcke ; Betreuer: Jochen Klucken
    Keywords Medizin, Gesundheit ; Medicine, Health
    Subject code sg610
    Language German
    Publisher Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
    Publishing place Erlangen
    Document type Book ; Online ; Thesis
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  8. Article ; Online: Die Geschichte des ‚Freezing-of-gait‘ beim Parkinson-Syndrom – vom Phänomen zum Symptom.

    Klucken, Jochen / Winkler, Juergen / Krüger, Rejko / Jost, Wolfgang

    Fortschritte der Neurologie-Psychiatrie

    2020  Volume 88, Issue 9, Page(s) 573–581

    Abstract: The background of the freezing-of-gait (FOG) phenomenon in Parkinson's syndrome is presented in this review. The following issues are addressed: characterization of the symptom freezing and its subtypes that challenge standardized diagnostic procedures; ... ...

    Title translation The history of Freezing-of-gait in Parkinson's disease - from phenomena to symptom.
    Abstract The background of the freezing-of-gait (FOG) phenomenon in Parkinson's syndrome is presented in this review. The following issues are addressed: characterization of the symptom freezing and its subtypes that challenge standardized diagnostic procedures; available assessment methods generating freezing-related parameters that not only support clinical studies but can also be applied in everyday care, and current therapy options. FOG exists in different subtypes, and clinical and diagnostic definitions are limited by subjective characterization and semi-standardized tests. FOG-specific drug options are not existing, apart from the optimization of dopaminergic medication, which may also be due to the poor discriminatory power of standardized diagnostics. This is also true for deep brain stimulation. Both of these therapeutic options may be due not only to the complex neural network alterations as a motor-control correlate of FOG, but also because of challenging diagnostic assessments methodologies. Innovative, wearable, sensor-based diagnostic strategies are currently being developed, and supportive therapies using tools and technologies focusing on 'cueing' are becoming increasingly well accepted. Even though high level evidence is missing, they provide a helpful treatment option for individualized therapy. It can be assumed that these options will become particularly popular due to technological progress and likely alter the everyday treatment challenges faced by doctors and therapists.
    MeSH term(s) Gait ; Gait Disorders, Neurologic/complications ; Gait Disorders, Neurologic/physiopathology ; Humans ; Parkinson Disease/complications ; Parkinson Disease/physiopathology
    Language German
    Publishing date 2020-09-21
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 625328-3
    ISSN 1439-3522 ; 0720-4299
    ISSN (online) 1439-3522
    ISSN 0720-4299
    DOI 10.1055/a-1227-6258
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  9. Article ; Online: Monitoring medication optimization in patients with Parkinson's disease.

    Moradi, Hamid / Hannink, Julius / Stallforth, Sabine / Gladow, Till / Ringbauer, Stefan / Mayr, Martin / Winkler, Jurgen / Klucken, Jochen / Eskofier, Bjoern M

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

    2023  Volume 2023, Page(s) 1–4

    Abstract: Medication optimization is a common component of the treatment strategy in patients with Parkinson's disease. As the disease progresses, it is essential to compensate for the movement deterioration in patients. Conventionally, examining motor ... ...

    Abstract Medication optimization is a common component of the treatment strategy in patients with Parkinson's disease. As the disease progresses, it is essential to compensate for the movement deterioration in patients. Conventionally, examining motor deterioration and prescribing medication requires the patient's onsite presence in hospitals or practices. Home-monitoring technologies can remotely deliver essential information to physicians and help them devise a treatment decision according to the patient's need. Additionally, they help to observe the patient's response to these changes. In this regard, we conducted a longitudinal study to collect gait data of patients with Parkinson's disease while they received medication changes. Using logistic regression classifier, we could detect the annotated motor deterioration during medication optimization with an accuracy of 92%. Moreover, an in-depth examination of the best features illustrated a decline in gait speed and swing phase duration in the deterioration phases due to suboptimal medication.Clinical relevance- Our proposed gait analysis method in this study provides objective, detailed, and punctual information to physicians. Revealing clinically relevant time points related to the patient's need for medical adaption alleviates therapy optimization for physicians and reduces the duration of suboptimal treatment for patients. As the home-monitoring system acts remotely, embedding it in the medical care pathways could improve patients' quality of life.
    MeSH term(s) Humans ; Parkinson Disease/drug therapy ; Longitudinal Studies ; Quality of Life ; Monitoring, Physiologic ; Movement
    Language English
    Publishing date 2023-12-11
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2694-0604
    ISSN (online) 2694-0604
    DOI 10.1109/EMBC40787.2023.10340618
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  10. Article ; Online: The effects of an individualized smartphone-based exercise program on self-defined motor tasks in Parkinson's disease: a long-term feasibility study.

    Lützow, Lisa / Teckenburg, Isabelle / Koch, Veronika / Marxreiter, Franz / Jukic, Jelena / Stallforth, Sabine / Regensburger, Martin / Winkler, Jürgen / Klucken, Jochen / Gaßner, Heiko

    Journal of patient-reported outcomes

    2023  Volume 7, Issue 1, Page(s) 106

    Abstract: Background: Exercise therapy is considered effective for the treatment of motor impairment in patients with Parkinson's disease (PD). During the COVID-19 pandemic, training sessions were cancelled and the implementation of telerehabilitation concepts ... ...

    Abstract Background: Exercise therapy is considered effective for the treatment of motor impairment in patients with Parkinson's disease (PD). During the COVID-19 pandemic, training sessions were cancelled and the implementation of telerehabilitation concepts became a promising solution. The aim of this controlled interventional feasibility study was to evaluate the long-term acceptance and to explore initial effectiveness of a digital, home-based, high-frequency exercise program for PD patients. Training effects were assessed using patient-reported outcome measures combined with sensor-based and clinical scores.
    Methods: 16 PD patients (smartphone group, SG) completed a home-based, individualized training program over 6-8 months using a smartphone app, remotely supervised by a therapist, and tailored to the patient's motor impairments and capacity. A control group (CG, n = 16) received medical treatment without participating in digital exercise training. The usability of the app was validated using System Usability Scale (SUS) and User Version of the Mobile Application Rating Scale (uMARS). Outcome measures included among others Unified Parkinson Disease Rating Scale, part III (UPDRS-III), sensor-based gait parameters derived from standardized gait tests, Parkinson's Disease Questionnaire (PDQ-39), and patient-defined motor activities of daily life (M-ADL).
    Results: Exercise frequency of 74.5% demonstrated high adherence in this cohort. The application obtained 84% in SUS and more than 3.5/5 points in each subcategory of uMARS, indicating excellent usability. The individually assessed additional benefit showed at least 6 out of 10 points (Mean = 8.2 ± 1.3). From a clinical perspective, patient-defined M-ADL improved for 10 out of 16 patients by 15.5% after the training period. The results of the UPDRS-III remained stable in the SG while worsening in the CG by 3.1 points (24%). The PDQ-39 score worsened over 6-8 months by 83% (SG) and 59% (CG) but the subsection mobility showed a smaller decline in the SG (3%) compared to the CG (77%) without reaching significance level for all outcomes. Sensor-based gait parameters remained constant in both groups.
    Conclusions: Long-term training over 6-8 months with the app is considered feasible and acceptable, representing a cost-effective, individualized approach to complement dopaminergic treatment. This study indicates that personalized, digital, high-frequency training leads to benefits in motor sections of ADL and Quality of Life.
    MeSH term(s) Humans ; Parkinson Disease/therapy ; Quality of Life ; Smartphone ; Feasibility Studies ; Pandemics ; Treatment Outcome ; Exercise Therapy/methods ; Exercise
    Language English
    Publishing date 2023-10-30
    Publishing country Germany
    Document type Journal Article
    ISSN 2509-8020
    ISSN (online) 2509-8020
    DOI 10.1186/s41687-023-00631-6
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