A5080416734- Cancer Genomics and Diagnostics
- Scientific Computing and Data Management
- Biomedical Text Mining and Ontologies
- Radiomics and Machine Learning in Medical Imaging
- Bioinformatics and Genomic Networks
- Artificial Intelligence in Healthcare and Education
- Machine Learning in Healthcare
- Genomics and Rare Diseases
- Electronic Health Records Systems
- Health and Medical Studies
- Immunotherapy and Immune Responses
- Genetic factors in colorectal cancer
- Cancer Immunotherapy and Biomarkers
- Ethics in Clinical Research
- Cardiac electrophysiology and arrhythmias
- Genetic Associations and Epidemiology
- Immune Cell Function and Interaction
- Data Quality and Management
- HER2/EGFR in Cancer Research
- Rheumatoid Arthritis Research and Therapies
- Pancreatic and Hepatic Oncology Research
- Gastrointestinal disorders and treatments
- Semantic Web and Ontologies
- Colorectal Cancer Treatments and Studies
- Healthcare Technology and Patient Monitoring
Martin Luther University Halle-Wittenberg
2021-2025
Friedrich-Alexander-Universität Erlangen-Nürnberg
2016-2025
Bio-Medical Science (South Korea)
2024
Luther University
2024
University Medical Center of the Johannes Gutenberg University Mainz
2024
Johannes Gutenberg University Mainz
2024
University Hospital in Halle
2024
Wittenberg University
2024
Philip Morris International (Germany)
2023
Wuhan National Laboratory for Optoelectronics
2022
Advanced colorectal carcinoma (CRC) is characterized by a high frequency of primary immune evasion and refractoriness to immunotherapy. Given the importance interferon (IFN)-γ in CRC immunosurveillance, we investigated whether how acquired IFN-γ resistance tumor cells would promote growth, sensitivity could be restored.Spontaneous colitis-associated development was induced mice with specific pathway inhibition intestinal epithelial cells. The influence gene status expression on survival...
Molecular tumor boards (MTBs) play a pivotal role in personalized oncology, leveraging complex data sets to tailor therapy for cancer patients. The integration of digital support and visualization tools is essential this rapidly evolving field facing fast-growing changing clinical processes. This study addresses the gap understanding evolution software needs within MTBs evaluates current state support. Alignment between user requirements development crucial avoid waste resources maintain...
Background: The cBioPortal is a prevalent open-source translational research platform, allowing private instances and extensions.
(1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge both bioinformatics oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses annotation NGS data including quality control, alignment, calling, copy number variation estimation, evaluation...
Clinicians in molecular tumor boards (MTB) are confronted with a growing amount of genetic high-throughput sequencing data. Today, at German university hospitals, these data usually handled complex spreadsheets from which clinicians have to obtain the necessary information. The aim this work was gather comprehensive list requirements be met by cBioPortal support processes MTBs according clinical needs. Therefore, oncology experts nine hospitals were surveyed two rounds interviews. To...
Gastrointestinal stromal tumors (GISTs) are rare malignancies but the most common mesenchymal of digestive tract. Recent advances in diagnostic imaging and an increasing incidence will confront us more frequently with tumors. This single center study aimed to characterize GIST patients terms tumor location, clinical presentation, metastasis formation, as well associated secondary malignancies.In a retrospective study, 104 histologically confirmed diagnosis GIST, collected between 1993 2011,...
Colorectal cancer (CRC) is one of the leading causes cancer-related deaths worldwide and need for novel biomarkers therapeutic strategies to improve diagnosis surveillance obvious. This study aims identify β6 -integrin (ITGB6) as a serum tumor marker diagnosis, prognosis, CRC. ITGB6 levels were validated in retro- prospective CRC patient cohorts. analyzed by ELISA. Using an initial cohort 60 patients, we found that present CRC, but not non-CRC control patients. A cut-off ≥2 ng/mL reveals...
Molecular tumor boards (MTBs) cope with the complexity of an increased usage genome sequencing data in cancer treatment. As for most these patients, guideline-based therapy options are exhausted, finding matching clinical trials is crucial. This search process often performed manually and therefore time consuming complex due to heterogeneous challenging dataset.
Background Artificial intelligence (AI) is increasingly used in medical care, particularly the areas of image recognition and processing. While its practical use other still limited, an understanding patients’ needs essential for sustainable implementation AI, which could further acceptance new innovations. Objective The objective this study was to explore perceptions toward acceptance, challenges implementation, potential applications AI care. Methods a qualitative research design. To...
The rise of artificial intelligence (AI) in medical care presents several opportunities, including improving patient outcomes. As part the PEAK project (Perspectives on Use and Acceptance Artificial Intelligence Medical Care), this study aimed to examine general population's technology affinity perceptions regarding AI their treatment using questionnaire data from population-based online panel HeReCa (Health Related Beliefs Health Care Experiences Germany). In principle, participants were...
Patient similarity analysis is pivotal in cancer research and clinical oncology, aiding identifying patterns among patients with similar molecular profiles to guide therapeutic decisions, particularly Molecular Tumor Boards (MTB), where therapy decisions are frequently informed by the treatment experiences of previously treated patients. However, lack standardized tools for automation visualization limits efficiency here, especially individualized MTB decisions. This study aims develop a...
Molecular tumor boards present special challenges when it comes to information collection for case preparation. It is one of the most time-consuming tasks participating pathologists and oncologists face, limiting number cases that can be discussed in these specialized turn profit from a potential highly personalized therapy. Digital support necessity enable medical professionals efficiently make use vast amount data available each patient their genomic clinical profile. This includes...
Abstract Background The increasing availability of molecular and clinical data cancer patients combined with novel machine learning techniques has the potential to enhance decision support, example, for assessing a patient's relapse risk. While these prediction models often produce promising results, deployment in settings is rarely pursued. Objectives In this study, we demonstrate how tools can be integrated generically into setting provide an exemplary use case predicting risk melanoma...
Background The introduction of next-generation sequencing (NGS) into molecular cancer diagnostics has led to an increase in the data available for identification and evaluation driver mutations defining personalized treatment regimens. meaningful combination omics data, ie, pathogenic gene variants alterations with other patient understand full picture malignancy been challenging. Objective This study describes implementation a system capable processing, analyzing, subsequently combining NGS...
In Molecular Tumor Boards (MTBs), therapy recommendations for cancer patients are discussed. To aid decision-making based on the patient’s molecular profile, research platform cBioPortal was extended users’ requirements. Additionally, a comprehensive dockerized workflow developed to support deployment of and connected services. this work, we present challenges experiences nearly two years implementing deploying an MTB compare those findings previous study.
This paper presents a biobanking IT framework, comprising set of integrated information technology components. It provides adaptable and scalable support for varying scenarios, workflows projects, while avoiding redundancy in data technology. Feasibility this approach is illustrated by implementations four different projects at Erlangen University Hospital with cooperating partners Münster Lübeck.
Artificial intelligence (AI) in medicine is a very topical issue. As far as the attitudes and perspectives of different stakeholders healthcare are concerned, there still much to be explored.Our aim was determine aspects towards acceptance AI applications from perspective physicians university hospitals.We conducted individual exploratory expert interviews. Low fidelity mockups were used show interviewees potential application areas clinical care.In principle, open use medical care. However,...
Description The Open Source software i2b2 [1] provides a translational research platform for storing biomedical data and querying these with user-friendly interface researchers (Figure 1). Despite its powerful features, it is lacking tools installation configuration, the import of source creation comprehensive navigational structure (i2b2 ontology). To close gaps, Integrated Data Repository Toolkit (IDRT), consisting three tools, has been created. Wizard shell GUI configuration instances,...
Using gene markers and other patient features to predict clinical outcomes plays a vital role in enhancing decision making improving prognostic accuracy. This work uses large set of colorectal cancer data train predictive models using machine learning methods such as random forest, general linear model, neural network for clinically relevant including disease free survival, radio-chemotherapy response (RCT-R) relapse. The most successful were created dichotomous like relapse RCT-R with...