A method for interoperable knowledge-based data quality assessment.

Background: Assessing the quality of healthcare data is a complex task including the selection of suitable measurement methods (MM) and adequately assessing their results.

Objectives: To present an interoperable data quality (DQ) assessment method that formalizes MMs based on standardized data definitions and intends to support collaborative governance of DQ-assessment knowledge, e.g.

ASimulatoR: splice-aware RNA-Seq data simulation.

Summary: A plethora of tools exist for RNA-Seq data analysis with a focus on alternative splicing (AS). However, appropriate data for their comparative evaluation is missing. The R package ASimulatoR simulates gold standard RNA-Seq datasets with fine-grained control over the distribution of AS events, which allow for evaluating alternative splicing tools, e.

Clinical evaluation of an interoperable clinical decision-support system for the detection of systemic inflammatory response syndrome in critically ill children.

Background: Systemic inflammatory response syndrome (SIRS) is defined as a non-specific inflammatory process in the absence of infection. SIRS increases susceptibility for organ dysfunction, and frequently affects the clinical outcome of affected patients. We evaluated a knowledge-based, interoperable clinical decision-support system (CDSS) for SIRS detection on a pediatric intensive care unit (PICU).

EASL position paper on the use of COVID-19 vaccines in patients with chronic liver diseases, hepatobiliary cancer and liver transplant recipients.

According to a recent World Health Organization estimate, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, which originated in China in 2019, has spread globally, infecting nearly 100 million people worldwide by January 2021. Patients with chronic liver diseases (CLD), particularly cirrhosis, hepatobiliary malignancies, candidates for liver transplantation, and immunosuppressed individuals after liver transplantation appear to be at increased risk of infections in general, which in turn translates into increased mortality. This is also the case for SARS-CoV-2 infection, where patients with cirrhosis, in particular, are at high risk of a severe COVID-19 course.

A Deep Learning Approach for TUG and SPPB Score Prediction of (Pre-) Frail Older Adults on Real-Life IMU Data.

Since older adults are prone to functional decline, using Inertial-Measurement-Units (IMU) for mobility assessment score prediction gives valuable information to physicians to diagnose changes in mobility and physical performance at an early stage and increases the chances of rehabilitation. This research introduces an approach for predicting the score of the Timed Up & Go test and Short-Physical-Performance-Battery assessment using IMU data and deep neural networks. The approach is validated on real-world data of a cohort of 20 frail or (pre-) frail older adults of an average of 84.

Health-Enabling Technologies to Assist Patients With Musculoskeletal Shoulder Disorders When Exercising at Home: Scoping Review.

Background: Health-enabling technologies (HETs) are information and communication technologies that promote individual health and well-being. An important application of HETs is telerehabilitation for patients with musculoskeletal shoulder disorders. Currently, there is no overview of HETs that assist patients with musculoskeletal shoulder disorders when exercising at home.

Unobtrusive Health Monitoring in Private Spaces: The Smart Home.

With the advances in sensor technology, big data, and artificial intelligence, unobtrusive in-home health monitoring has been a research focus for decades. Following up our research on smart vehicles, within the framework of unobtrusive health monitoring in private spaces, this work attempts to provide a guide to current sensor technology for unobtrusive in-home monitoring by a literature review of the state of the art and to answer, in particular, the questions: (1) What types of sensors can be used for unobtrusive in-home health data acquisition? (2) Where should the sensors be placed? (3) What data can be monitored in a smart home? (4) How can the obtained data support the monitoring functions? We conducted a retrospective literature review and summarized the state-of-the-art research on leveraging sensor technology for unobtrusive in-home health monitoring. For structured analysis, we developed a four-category terminology (location, unobtrusive sensor, data, and monitoring functions).

Enabling single-cell trajectory network enrichment.

Single-cell sequencing (scRNA-seq) technologies allow the investigation of cellular differentiation processes with unprecedented resolution. Although powerful software packages for scRNA-seq data analysis exist, systems biology-based tools for trajectory analysis are rare and typically difficult to handle. This hampers biological exploration and prevents researchers from gaining deeper insights into the molecular control of developmental processes.

Adaptive learning and cross training improves R-wave detection in ECG.

Background And Objective: Automated R-wave detection plays a vital role in electrocardiography (ECG) and ECG-based computer-aided diagnosis. Recently, a multi-level one-dimensional (1D) deep learning approach was presented that shows good performance as compared to traditional methods.

Methods: In this paper, we present several improvements of the multi-level 1D convolutional neural network (CNN)-based deep learning approach using: (i) adaptive deep learning, (ii) cross-database training, and (iii) cross-lead training.

A Novel Triple-Fluorescent HCMV Strain Reveals Gene Expression Dynamics and Anti-Herpesviral Drug Mechanisms.

Human Cytomegalovirus (HCMV) infection may result in severe outcomes in immunocompromised individuals such as AIDS patients, transplant recipients, and neonates. To date, no vaccines are available and there are only few drugs for anti-HCMV therapy. Adverse effects and the continuous emergence of drug-resistance strains require the identification of new drug candidates in the near future.

BiCoN: network-constrained biclustering of patients and omics data.

Motivation: Unsupervised learning approaches are frequently used to stratify patients into clinically relevant subgroups and to identify biomarkers such as disease-associated genes. However, clustering and biclustering techniques are oblivious to the functional relationship of genes and are thus not ideally suited to pinpoint molecular mechanisms along with patient subgroups.

Results: We developed the network-constrained biclustering approach Biclustering Constrained by Networks (BiCoN) which (i) restricts biclusters to functionally related genes connected in molecular interaction networks and (ii) maximizes the difference in gene expression between two subgroups of patients.

Acceptance Study on the Usage of Health-Enabling Technologies in Therapy and Diagnostics for People with Mental Disorders.

Mental disorders are widespread among the world's population and place a high burden on both the people affected and the economy. In this area of health care and prevention major deficits can be found. Health-enabling technologies are being developed in order to provide support in the therapy and diagnostics of mental disorders.

International Comparison of Six Basic eHealth Indicators Across 14 Countries: An eHealth Benchmarking Study.

Background: Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country.

Intestinal Dysbiosis Amplifies Acetaminophen-Induced Acute Liver Injury.

Background & Aims: Acute liver failure (ALF) represents an unmet medical need in Western countries. Although the link between intestinal dysbiosis and chronic liver disease is well-established, there is little evidence for a functional role of gut-liver interaction during ALF. Here we hypothesized that intestinal dysbiosis may affect ALF.

NOX5-induced uncoupling of endothelial NO synthase is a causal mechanism and theragnostic target of an age-related hypertension endotype.

Hypertension is the most important cause of death and disability in the elderly. In 9 out of 10 cases, the molecular cause, however, is unknown. One mechanistic hypothesis involves impaired endothelium-dependent vasodilation through reactive oxygen species (ROS) formation.

Synthetic rewiring and boosting type I interferon responses for visualization and counteracting viral infections.

Mammalian first line of defense against viruses is accomplished by the interferon (IFN) system. Viruses have evolved numerous mechanisms to reduce the IFN action allowing them to invade the host and/or to establish latency. We generated an IFN responsive intracellular hub by integrating the synthetic transactivator tTA into the chromosomal Mx2 locus for IFN-based activation of tTA dependent expression modules.

Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing.

Background: Merging disparate and heterogeneous datasets from clinical routine in a standardized and semantically enriched format to enable a multiple use of data also means incorporating unstructured data such as medical free texts. Although the extraction of structured data from texts, known as natural language processing (NLP), has been researched at least for the English language extensively, it is not enough to get a structured output in any format. NLP techniques need to be used together with clinical information standards such as openEHR to be able to reuse and exchange still unstructured data sensibly.

A Metric for Evaluating a Transformation of Subscription-Based Journals into Open-Access Journals.

Open Access is an upcoming paradigm to communicate scientific knowledge. The Trans-O-MIM Project works on strategies, models, and evaluation metrics for the goal-oriented, stepwise, sustainable, and fair transformation of established subscription-based scientific journals into open-access-based journals. This research intends to present an evaluation metric and the associated identified appropriate parameters for such transformations.

AGT-Reha-WK study: protocol for a non-inferiority trial comparing the efficacy and costs of home-based telerehabilitation for shoulder diseases with medical exercise therapy.

Introduction: Shoulder lesions rank among the top 15 diagnoses accounting for days of incapacity to work. Inpatient or full-day outpatient rehabilitation are some of the standard therapies. For sustainable rehabilitation, continuation of rehabilitation after discharge from a rehabilitation centre is vital.

Risk factors for Covid-19 severity and fatality: a structured literature review.

Purpose: Covid-19 is a global threat that pushes health care to its limits. Since there is neither a vaccine nor a drug for Covid-19, people with an increased risk for severe and fatal courses of disease particularly need protection. Furthermore, factors increasing these risks are of interest in the search of potential treatments.

Gamification in Rehabilitation of Patients With Musculoskeletal Diseases of the Shoulder: Scoping Review.

Background: Gamification has become increasingly important both in research and in practice. Particularly in long-term care processes, such as rehabilitation, playful concepts are gaining in importance to increase motivation and adherence. In addition to neurological diseases, this also affects the treatment of patients with musculoskeletal diseases such as shoulder disorders.

Notable Papers and Trends from 2019 in Sensors, Signals, and Imaging Informatics.

Objective: To highlight noteworthy papers that are representative of 2019 developments in the fields of sensors, signals, and imaging informatics.

Method: A broad literature search was conducted in January 2020 using PubMed. Separate predefined queries were created for sensors/signals and imaging informatics using a combination of Medical Subject Heading (MeSH) terms and keywords.

International Academy of Health Sciences Informatics (IAHSI): Strategy and Focus Areas, 1st Version.

Background: The International Academy of Health Sciences Informatics (IAHSI) is the Academy of the International Medical Informatics Association (IMIA). As an international forum for peers in biomedical and health informatics, the Academy shall play an important role in exchanging knowledge, providing education and training, and producing policy documents.

Objectives: A major priority of the Academy's activities in its inaugural phase was to define its strategy and focus areas in accordance with its objectives and to prioritize the Academy's work, which can then be transferred to respective taskforces.

Health-Enabling Technologies for Telerehabilitation of the Shoulder: A Feasibility and User Acceptance Study.

Background: After discharge from a rehabilitation center the continuation of therapy is necessary to secure already achieved healing progress and sustain (re-)integration into working life. To this end, home-based exercise programs are frequently prescribed. However, many patients do not perform their exercises as frequently as prescribed or even with incorrect movements.