Research Subjects and Research Trends in Medical Informatics.

Objectives: To identify major research subjects and trends in medical informatics research based on the current set of core medical informatics journals.

Methods: Analyzing journals in the Web of Science (WoS) medical informatics category together with related categories from the years 2013 to 2017 by using a smart local moving algorithm as a clustering method for identifying the core set of journals. Text mining analysis with binary counting of abstracts from these journals published in the years 2006 to 2017 for identifying major research subjects.

Measurement of the Chair Rise Performance of Older People Based on Force Plates and IMUs.

An early detection of functional decline with age is important to start interventions at an early state and to prolong the functional fitness. In order to assure such an early detection, functional assessments must be conducted on a frequent and regular basis. Since the five time chair rise test (5CRT) is a well-established test in the geriatric field, this test should be supported by technology.

Modulation of TAP-dependent antigen compartmentalization during human monocyte-to-DC differentiation.

Dendritic cells (DCs) take up antigen in the periphery, migrate to secondary lymphoid organs, and present processed antigen fragments to adaptive immune cells and thus prime antigen-specific immunity. During local inflammation, recirculating monocytes are recruited from blood to the inflamed tissue, where they differentiate to macrophages and DCs. In this study, we found that monocytes showed high transporter associated with antigen processing (TAP)-dependent peptide compartmentalization and that after antigen pulsing, they were not able to efficiently stimulate antigen-specific T lymphocytes.

INBED: A Highly Specialized System for Bed-Exit-Detection and Fall Prevention on a Geriatric Ward.

Objective: In geriatric institutions, the risk of falling of patients is very high and frequently leads to fractures of the femoral neck, which can result in serious consequences and medical costs. With regard to the current numbers of elderly people, the need for smart solutions for the prevention of falls in clinical environments as well as in everyday life has been evolving.

Methods: Hence, in this paper, we present the Inexpensive Node for bed-exit Detection (INBED), a comprehensive, favourable signaling system for bed-exit detection and fall prevention, to support the clinical efforts in terms of fall reduction.

Assessment of Decision Models for Hybrid Approaches.

A wide range of Clinical Decision Support Systems (CDSS) have been developed. These CDSS are based on decision models, which normally have a knowledge- or data-driven approach. In this work a structured development of potential hybrid approaches was realized by the assessment of decision models and identification of their advantages and disadvantages.

A Brief Survey on Six Basic and Reduced eHealth Indicators in Seven Countries in 2017.

Background: Holistic, ubiquitous support of patient-centered health care (eHealth) at all health care institutions and in patients' homes through information processing is increasingly supplementing institution-centered care. While eHealth indicators may measure the transition from institution-centered (e.g.

Deep Learning on 1-D Biosignals: a Taxonomy-based Survey.

Objectives:  Deep learning models such as convolutional neural networks (CNNs) have been applied successfully to medical imaging, but biomedical signal analysis has yet to fully benefit from this novel approach. Our survey aims at (i) reviewing deep learning techniques for biosignal analysis in computer- aided diagnosis; and (ii) deriving a taxonomy for organizing the growing number of applications in the field.

Methods:  A comprehensive literature research was performed using PubMed, Scopus, and ACM.

Visions for IAHSI, the International Academy of Health Sciences Informatics.

These visions for IAHSI, the newly founded International Academy of Health Sciences Informatics ("the Academy"), include the following principles, in order of descending priority: (1) The Academy should attempt to contribute to the health of the people in our world, (2) the Academy should be engaged in advising governments and organizations on developing health and science through informatics, (3) the Academy should stimulate progress in informatics research, education, and practice, (4) Academy members should share and exchange knowledge, (5) the Academy's structure and organization should follow the tradition of scientific societies, (6) Academy membership is one of the highest honors in informatics internationally, (7) the Academy should meet where the International Medical Informatics Association meets, and (8) the Academy's structure and organization should be lean and unbiased. These visions have been put forward for discussion specifically but not exclusively to the inaugural class of the Academy, organized at the 2018 Medical Informatics Europe conference, with its distinguished members.

Irregular, narrow-complex tachycardia.

The correct differentiation of an irregular, narrow-complex tachycardia has crucial implications for the therapeutic management of these conditions. In this article we present a differential diagnostic and treatment approach to irregular, narrow-complex tachycardias.

Striving for Use Case Specific Optimization of Data Quality Assessment for Health Data.

Data quality (DQ) assessment is advisable before (re)using datasets. Besides supporting DQ-assessment, DQ-tools can indicate data integration issues. The objective of this contribution is to put up for discussion the identified current state of scientific knowledge in DQ-assessment for health data and the planned work resulting from that state of knowledge.

Learning Healthcare Systems in Pediatrics: Cross-Institutional and Data-Driven Decision-Support for Intensive Care Environments (CADDIE).

Background: The vast amount of data generated in healthcare can be reused to support decision-making by developing clinical decision-support systems. Since evidence is lacking in Pediatrics, it seems to be beneficial to design future systems towards the vision of generating evidence through cross-institutional data analysis and continuous learning cycles.

Objectives: Presentation of an approach for cross-institutional and data-driven decision support in pediatric intensive care units (PICU), and the long-term vision of Learning Healthcare Systems in Pediatrics.

Advantages of Modular Hybrid Network Communication on Clinical Wards.

The ever-increasing flood of information, especially in the medical-clinical field, inter alia due to the increase of data-intensive mobile/wearable devices, is one of the biggest challenges of medical informatics. In this work different possibilities of the integration of wearable devices on the example of the development of a fall prevention system are presented and classified. We started with a commercial off-the-shelf one-on-one system (Shimmer/Arduino) using a Bluetooth connection, integrated via nurse call system as Human-Machine-Interface.

Automatic Detection of Depression by Using a Neural Network.

Depression is the most common psychiatric disorder worldwide, which affects more than 300 million people. We aimed to detect depressed patients and healthy people automatically. We work on the PHQ-9 questionnaires and reduced it to a PHQ-5 questionnaires with a new cut-off value of 8 to detect depressed patients.

Leveraging Aging in Place Through Sensor-Enhanced In-Home Monitoring.

Seniors expect to age in place, which means living in their own homes as long as possible with familiar facilities and environments. Due to the capability of continuous and unobtrusive monitoring, the sensor-enhanced in-ho monitoring is regarded as a promising solution to support aging in place. In this paper, by reviewing three influential projects in this field of in-home monitoring for aging in place, we present our opinions and suggestions on the development of informatics-supported aging in place for its practical application in healthcare such as diagnosis and nursing in the era of data science.

Spatial agreement of demineralized areas in quantitative light-induced fluorescence images and digital photographs.

Objectives: Previous work has shown qualitatively that detection of demineralized tooth areas (white spot lesions, WSLs) is more reliable in digital photographs (DP) as in quantitative light-induced fluorescence (QLF) images. Based on non-rigid, multimodal image registration, we now quantitatively compare manual and automatic markings in both modalities.

Methods: After braces removal, pairs of DP and QLF were acquired from 124 teeth of 31 patients.

An interoperable clinical decision-support system for early detection of SIRS in pediatric intensive care using openEHR.

Background: Clinical decision-support systems (CDSS) are designed to solve knowledge-intensive tasks for supporting decision-making processes. Although many approaches for designing CDSS have been proposed, due to high implementation costs, as well as the lack of interoperability features, current solutions are not well-established across different institutions. Recently, the use of standardized formalisms for knowledge representation as terminologies as well as the integration of semantically enriched clinical information models, as openEHR Archetypes, and their reuse within CDSS are theoretically considered as key factors for reusable CDSS.

Modeling of ETL-Processes and Processed Information in Clinical Data Warehousing.

Background: Literature describes a big potential for reuse of clinical patient data. A clinical data warehouse (CDWH) is a means for that.

Objectives: To support management and maintenance of processes extracting, transforming and loading (ETL) data into CDWHs as well as to ease reuse of metadata between regular IT-management, CDWH and secondary data users by providing a modeling approach.

Clinical Knowledge Governance Framework for Nationwide Data Infrastructure Projects.

Background: The availability of semantically-enriched and interoperable clinical information models is crucial for reusing once collected data across institutions like aspired in the German HiGHmed project. Funded by the Federal Ministry of Education and Research, this nationwide data infrastructure project adopts the openEHR approach for semantic modelling. Here, strong governance is required to define high-quality and reusable models.

Personalized Knowledge Transfer for Caregiving Relatives.

Caregiving relatives have to manage very diverse tasks and need a lot of care-relevant knowledge. For most of them it is not easy to find the knowledge required. Thus, a personalized knowledge transfer for caregiving relatives is necessary.

Semi-Automatically Measuring Shoulders' Range of Motion - Objective Measurements with Good Reliability and Accuracy.

The shoulder's range of motion (ROM) is an important measurement for the diagnostic process and course of treatment for patients with shoulder disorders or injuries. Visual estimation to assess a shoulder's ROM is a fast measuring method, and therefore routinely used in clinical practice. Studies already proved this method as very subjective and unreliable.

A Review of Decision Support Systems for Smart Homes in the Health Care System.

The use of decision support systems for smart homes can provide attractive solutions for challenges that have arisen in the Health Care System due to ageing of society. In order to provide an overview of current research projects in this field, a systematic literature review was performed according to the PRISMA approach. The aims of this work are to provide an overview of current research projects and to update a similar study from 2012.