Europe's Largest Research Infrastructure for Curated Medical Data Models with Semantic Annotations.

Background: Structural metadata from the majority of clinical studies and routine health care systems is currently not yet available to the scientific community.

Objective: To provide an overview of available contents in the Portal of Medical Data Models (MDM Portal).

Methods: The MDM Portal is a registered European information infrastructure for research and health care, and its contents are curated and semantically annotated by medical experts.

Architecture of the Mass Spectrometry Data Management Pipeline in the SMART-CARE Project.

In the SMART-CARE project- a systems medicine approach to stratification of cancer recurrence in Heidelberg, Germany - a streamlined mass-spectrometry (MS) workflow for identification of cancer relapse was developed. This project has multiple partners from clinics, laboratories and computational teams. For optimal collaboration, consistent documentation and centralized storage, the linked data repository was designed.

Next-generation study databases require FAIR, EHR-integrated, and scalable Electronic Data Capture for medical documentation and decision support.

Structured patient data play a key role in all types of clinical research. They are often collected in study databases for research purposes. In order to describe characteristics of a next-generation study database and assess the feasibility of its implementation a proof-of-concept study in a German university hospital was performed.

Proposing a Novel Hybrid Short-Term Exchange Program in Biomedical and Health Informatics Education.

International student exchange is a valuable opportunity for Biomedical and Health Informatics students to gain new perspectives and experiences. In the past, such exchanges have been made possible through international partnerships between universities. Unfortunately, numerous obstacles such as housing, financial concerns, and environmental implications related to travel, have made it difficult to continue international exchange.

Portal of Medical Data Models: Application in Federated Data Capture.

So far, the portal for medical data models allows its users to download medical forms in a standardized format. Importing data models into electronic data capture software involved a manual step of downloading and importing the files. Now, the portal was enhanced with a web services interface to allow electronic data capture systems to automatically download the forms.

Federated electronic data capture (fEDC): Architecture and prototype.

In clinical research as well as patient care, structured documentation of findings is an important task. In many cases, this is achieved by means of electronic case report forms (eCRF) using corresponding information technology systems. To avoid double data entry, eCRF systems can be integrated with electronic health records (EHR).

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia.

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68).

Towards Data Analysis Environment for Multi-Partner Clinical Research Project - SMART-CARE.

A Systems Medicine Approach to Stratification of Cancer Recurrence (SMART-CARE) establishes mass spectrometry-based systems medicine technologies and data analysis pipelines employing expertise of the multiple partners from Heidelberg biomedical campus. We have established a central linked data repository that links clinical, mass spectrometry, and data analysis teams to enable a full cycle of data management. Other questions of setting up the data analysis environment for the multi-partner clinical research project are addressed in this work, too.

Data Management for Systems Medicine: The SMART-CARE Joint Environment.

For a research project on mass spectrometry, a streamlined, harmonized and robust analytical pipeline is built to predict tumor recurrence. By means of standardization all steps from sample collection, analysis, proteome, and metabolome analysis are harmonized. Challenges like non-central identificators and distributed data are overcome with a centralized high-performant IT-platform in combination with a pseudonymization service and harmonization.

On the Construction of Multilingual Corpora for Clinical Text Mining.

The amount of digital data derived from healthcare processes have increased tremendously in the last years. This applies especially to unstructured data, which are often hard to analyze due to the lack of available tools to process and extract information. Natural language processing is often used in medicine, but the majority of tools used by researchers are developed primarily for the English language.

vivaGen - a survival data set generator for software testing.

An amendment to this paper has been published and can be accessed via the original article.

Graph-Representation of Patient Data: a Systematic Literature Review.

Graph theory is a well-established theory with many methods used in mathematics to study graph structures. In the field of medicine, electronic health records (EHR) are commonly used to store and analyze patient data. Consequently, it seems straight-forward to perform research on modeling EHR data as graphs.

Methods for a similarity measure for clinical attributes based on survival data analysis.

Background: Case-based reasoning is a proven method that relies on learned cases from the past for decision support of a new case. The accuracy of such a system depends on the applied similarity measure, which quantifies the similarity between two cases. This work proposes a collection of methods for similarity measures especially for comparison of clinical cases based on survival data, as they are available for example from clinical trials.

A Concept for Graph-Based Temporal Similarity of Patient Data.

Computer-based decision support systems are often used for dedicated tasks such as the detection of sepsis. However, positive predictive values for sepsis detection are reported to achieve only around 46%. In this paper we describe a novel approach to use temporal data of electronic patient records based on similarity measures.

Optimization of Clinical Decision Support Based on Pearson Correlation of Attributes.

Clinical decision support is very important especially in such a wide-spread disease as a coronary artery disease. A large variety of prediction methods can potentially solve the classification problem to support clinical decisions. However, not all of them provide similar efficiency for the classification of patients with coronary artery disease.

Extraction from Medical Records.

Despite using electronic medical records, free narrative text is still widely used for medical records. Such text cannot be analyzed by statistical tools and be proceed by decision support systems. To make data from texts available for such tasks a supervised machine learning algorithms might be successfully applied.

Implementing Systems Medicine: A Medical Informatics Perspective.

Systems medicine is a paradigm for translating in silico methods developed for modelling biological systems into the field of medicine. Such approaches rely on the integration of as many data sources as possible, both in the dimension of disease knowledge and patient data. This is a challenging task that can only be implemented in clinical routine with the help of suitable information technology from the field of Medical Informatics.

From Bench to Bedside: A View on Bioinformatics Pipelines.

Although sequencing technology has become widely available in recent years, the steps in bioinformatics pipelines are time-consuming and barely standardized. New tools to improve individual steps in a pipeline are frequently published and configurations can be quickly adapted to use new versions. We performed case studies with a representative set of pipeline management tools using the GEP-R pipeline, and a qualitative study of different software packages covering relevant classes of software tools.

The Use of Tools, Modelling Methods, Data Types, and Endpoints in Systems Medicine: A Survey on Projects of the German e:Med-Programme.

Systems medicine is the consequent continuation of research efforts on the road to an individualized medicine. Thereby, systems medicine tries to offer a holistic view on the patient by combining different data sources to highlight different perspectives on the patient's health. Our research question was to identify the main data types, modelling methods, analysis tools, and endpoints currently used and studied in systems medicine.

Unlocking Data for Statistical Analyses and Data Mining: Generic Case Extraction of Clinical Items from i2b2 and tranSMART.

In medical science, modern IT concepts are increasingly important to gather new findings out of complex diseases. Data Warehouses (DWH) as central data repository systems play a key role by providing standardized, high-quality and secure medical data for effective analyses. However, DWHs in medicine must fulfil various requirements concerning data privacy and the ability to describe the complexity of (rare) disease phenomena.

Automated Classification of Selected Data Elements from Free-text Diagnostic Reports for Clinical Research.

Objectives: In the Multiple Myeloma clinical registry at Heidelberg University Hospital, most data are extracted from discharge letters. Our aim was to analyze if it is possible to make the manual documentation process more efficient by using methods of natural language processing for multiclass classification of free-text diagnostic reports to automatically document the diagnosis and state of disease of myeloma patients. The first objective was to create a corpus consisting of free-text diagnosis paragraphs of patients with multiple myeloma from German diagnostic reports, and its manual annotation of relevant data elements by documentation specialists.

Systems Medicine for Multiple Myeloma: A Review on Decision Support Systems.

Systems medicine is a current approach trying to improve treatment for patients with complex diseases by analyzing as much phenotype and genotype data as possible for the disease in question. For individualized treatment decisions in clinical practice, this task has to be supported by an application system with decision support component. For a research project on systems medicine we reviewed methods for decision support.