A5042665782- Peripheral Neuropathies and Disorders
- Myasthenia Gravis and Thymoma
- Multiple Sclerosis Research Studies
- Artificial Intelligence in Healthcare and Education
- Health and Medical Studies
- Biomedical Text Mining and Ontologies
- Hereditary Neurological Disorders
- Digital Mental Health Interventions
- COVID-19 diagnosis using AI
- Neurological disorders and treatments
- Antiplatelet Therapy and Cardiovascular Diseases
- interferon and immune responses
- Immune Cell Function and Interaction
- Meta-analysis and systematic reviews
- Sphingolipid Metabolism and Signaling
- Inflammatory Myopathies and Dermatomyositis
- Neuroethics, Human Enhancement, Biomedical Innovations
- Long-Term Effects of COVID-19
- Cancer therapeutics and mechanisms
- Rheumatoid Arthritis Research and Therapies
- Cytokine Signaling Pathways and Interactions
- Social Policies and Healthcare Reform
- Toxin Mechanisms and Immunotoxins
- Social and Demographic Issues in Germany
- Machine Learning in Healthcare
Düsseldorf University Hospital
2021-2025
Heinrich Heine University Düsseldorf
2021-2025
Hasso Plattner Institute
2022-2024
University of Potsdam
2022-2024
University Hospital Münster
2020-2021
Digital Health Technologies (DHTs) such as connected sensors offer particular promise for improving data collection and patient empowerment in neurology research care. This study analyzed the recent evolution of use DHTs trials registered on ClinicalTrials.gov four chronic neurological disorders: epilepsy, multiple sclerosis, Alzheimer's, Parkinson's disease. We document growth both more established digital measures (e.g., motor function) novel speech) over years, highlighting contexts key trends.
Background Large language models (LLMs) have demonstrated impressive performances in various medical domains, prompting an exploration of their potential utility within the high-demand setting emergency department (ED) triage. This study evaluated triage proficiency different LLMs and ChatGPT, LLM-based chatbot, compared to professionally trained ED staff untrained personnel. We further explored whether LLM responses could guide effective Objective aimed assess efficacy associated product...
Abstract The 2019 German Digital Healthcare Act introduced the Health Application program, known in as ‘Digitale Gesundheitsanwendungen’ (DiGA). program has established a pioneering model for integrating Therapeutics (DTx) into healthcare system with scalable and effective reimbursement strategies. To date, continuous upward trend enabled by this framework resulted more than 374,000 DiGA prescriptions, increasingly cementing its role system. This perspective provides synthesis of program’s...
Effectively managing evidence-based information is increasingly challenging. This study tested large language models (LLMs), including document- and online-enabled retrieval-augmented generation (RAG) systems, using 13 recent neurology guidelines across 130 questions. Results showed substantial variability. RAG improved accuracy compared to base but still produced potentially harmful answers. RAG-based systems performed worse on case-based than knowledge-based Further refinement regulation...
Ocrelizumab is a B cell-depleting drug widely used in relapsing-remitting multiple sclerosis (RRMS) and primary-progressive MS. In RRMS, it becoming increasingly apparent that accumulation of disability not only manifests as relapse-associated worsening (RAW) but also progression independent relapse activity (PIRA) throughout the disease course. This study's objective was to investigate role PIRA RRMS patients treated with ocrelizumab. We performed single-center, retrospective,...
Digital therapeutics (DTx), evidence-based software interventions for preventing, managing, or treating medical disorders, have rapidly evolved with healthcare's shift toward online, patient-centric solutions. This study scrutinizes DTx clinical trials from 2005 to 2022, analyzing their growth, funding, underlying specialties, and other R&D characteristics, using ClinicalTrials.gov data. Our analysis includes categorized via the ICD-11 system, covering active, recruiting, completed studies...
Abstract Background Immune dysregulation is a hallmark of autoimmune diseases the central nervous system (CNS), characterized by an excessive immune response, and primary CNS tumors (pCNS-tumors) showing highly immunosuppressive parenchymal microenvironment. Methods Aiming to provide novel insights into pathogenesis autoimmunity cerebral tumor immunity, we analyzed peripheral blood (PB) cerebrospinal fluid (CSF) 81 limbic encephalitis (ALE), 148 relapsing–remitting multiple sclerosis (RRMS),...
Due to the growing complexity in monitoring and treatment of many disorders, disease-specific care research networks offer patients certified healthcare. However, networks' ability provide health services close patients' homes usually remains vague. Digital Health Technologies (DHTs) help better care, especially if implemented a targeted manner regions undersupplied by specialised networks. Therefore, we used car travel time-based isochrone approach identify gaps using example...
Cyclic GMP-AMP-synthase is a sensor of endogenous nucleic acids, which subsequently elicits stimulator interferon genes (STING)-dependent type I (IFN) response defending us against viruses and other intracellular pathogens. This pathway can drive pathological inflammation, as documented for interferonopathies. In contrast, specific STING activation subsequent IFN-β release have shown beneficial effects on experimental autoimmune encephalomyelitis (EAE) model multiple sclerosis (MS). Although...
Chronic inflammatory demyelinating polyneuropathy (CIDP) is an disease affecting the peripheral nerves and most frequent autoimmune polyneuropathy. Given lack of established biomarkers or risk factors for development CIDP patients' treatment response, this research effort seeks to identify potential clinical that may influence progression overall efficacy.
Abstract Introduction Chronic inflammatory demyelinating polyneuropathy (CIDP) is one of the most common immune neuropathies leading to severe impairments in daily life. Current treatment options include intravenous immunoglobulins (IVIG), which are administered at intervals 4–12 weeks. Determination individual challenging since existing clinical scores lack sensitivity objectify small, partially fluctuating deficits patients. End-of-dose phenomena described by patients, manifested increased...
The medical care of patients with myositis is a great challenge in clinical practice. This due to the rarity these disease, complexity diagnosis and management as well lack systematic analyses.Therefore, aim this project was obtain an overview current Germany evaluate epidemiological trends recent years.In collaboration BARMER Insurance, retrospective analysis outpatient inpatient data from average approximately 8.7 million insured between January 2005 December 2019 performed using ICD-10...
Aside from the established immune-mediated etiology of multiple sclerosis (MS), compelling evidence implicates platelets as important players in disease pathogenesis. Specifically, numerous studies have highlighted that activated promote central nervous system (CNS)-directed adaptive immune response early course. Platelets, therefore, present a novel opportunity for modulating neuroinflammatory process characterizes MS. We hypothesized well-known antiplatelet agent acetylsalicylic acid (ASA)...
Immune-mediated peripheral nervous system (PNS) disorders pose diagnostic and therapeutic challenges, necessitating collaborative, patient-centered care. Limited access to specialized centers leads delayed diagnosis care, as seen during the COVID-19 pandemic. To address these accessible care is crucial. On-site support plays a vital role in advising assisting patients caregivers, enabling multidisciplinary for PNS diseases.
Recent years have seen a rapid growth in the number of online health communities targeted at patients with long-term conditions. Myasthenia Gravis (MG) is rare neurological disease for which such not been analysed before. The aim this study was to better understand needs MG population through collation and categorisation questions that users social media were asking fellow on these platforms.
<sec> <title>BACKGROUND</title> Large language models (LLMs) have demonstrated impressive performances in various medical domains, prompting an exploration of their potential utility within the high-demand setting emergency department (ED) triage. This study evaluated triage proficiency different LLMs and ChatGPT, LLM-based chatbot, compared to professionally trained ED staff untrained personnel. We further explored whether LLM responses could guide effective </sec> <title>OBJECTIVE</title>...