COVID-19 Mobile Apps Trends Derived from Long-Term Google Play Analysis.

In this paper, we describe the 5-year trends of COVID-related mobile apps in the Google Play platform obtained by retrospectively analyzing app descriptions. Out of 21764 and 48750 unique apps available free of charge in the "medical" and "health and fitness", there were 161 and 143 COVID-related apps, respectively. The prominentrise in apps' prevalence occurred in January 2021.

Evaluation of a semiautomated App Store analysis for the identification of health apps for cardiac arrhythmias.

Background: Smartphone apps are increasingly utilised by patients and physicians for medical purposes. Thus, numerous applications are provided on the App Store platforms.

Objectives: The aim of the study was to establish a novel, expanded approach of a semiautomated retrospective App Store analysis (SARASA) to identify and characterise health apps in the context of cardiac arrhythmias.

The Minimum Feature Set for Designing Mobile Apps to Support Bipolar Disorder-Affected Patients: Proposal of Essential Functions and Requirements.

Research conducted on mobile apps providing mental health services has concluded that patients with mental disorders tend to use such apps to maintain mental health balance technology may help manage and monitor issues like bipolar disorder (BP). This study was conducted in four steps to identify the features of designing a mobile application for BP-affected patients including (1) a literature search, (2) analyzing existing mobile apps to examine their efficiency, (3) interviewing patients affected with BP to discover their needs, and 4) exploring the points of view of experts using a dynamic narrative survey. Literature search and mobile app analysis resulted in 45 features, which were later reduced to 30 after the experts were surveyed about the project.

Developing a mobile health application for wound telemonitoring: a pilot study on abdominal surgeries post-discharge care.

Background: Many early signs of Surgical Site Infection (SSI) developed during the first thirty days after discharge remain inadequately recognized by patients. Hence, it is important to use interactive technologies for patient support in these times. It helps to diminish unnecessary exposure and in-person outpatient visits.

Alternative splicing analysis benchmark with DICAST.

Alternative splicing is a major contributor to transcriptome and proteome diversity in health and disease. A plethora of tools have been developed for studying alternative splicing in RNA-seq data. Previous benchmarks focused on isoform quantification and mapping.

How to measure staff continuity in intensive psychiatric home treatment: a routine data and single case analysis.

Background: Intensive forms of outreach mental health care (IOC) such as crisis resolution or home treatment teams are increasingly implemented as alternatives to inpatient admission, providing recovery-oriented treatment at home at comparable costs and outcomes. However, one issue with IOC is the lack of continuity regarding staff members who provide home visits, complicating relationship building and meaningful therapeutic exchange. The aim of this study is to validate existing primarily qualitative findings using performance data and to explore a possible correlation between the number of staff involved within IOC treatment and the service users' length of stay (LOS).

Responsibility and decision-making authority in using clinical decision support systems: an empirical-ethical exploration of German prospective professionals' preferences and concerns.

Machine learning-driven clinical decision support systems (ML-CDSSs) seem impressively promising for future routine and emergency care. However, reflection on their clinical implementation reveals a wide array of ethical challenges. The preferences, concerns and expectations of professional stakeholders remain largely unexplored.

First Contact, First Learnings - Nursing Staff Approaching Robotics in Health Care.

Systems for service and assistance robotics become relevant in nursing care. Workshops with target user groups can support the reflection and identification of scenarios for the use of robotic systems.

Evidence of Digital Health Applications from a State-Regulated Repository for Reimbursable Health Applications in Germany.

17 RCTs for 15 digital health applications (DiGA) permanently listed in the state-regulated register were analyzed descriptively for methodological study aspects relevant to evidence analysis. The analysis revealed that several underlying studies had limitations, at least worthy of discussion, in terms of their power concerning sample size, intervention and control group specifications, drop-out rates, and blinding.

Medical Apps for Android and iOS: Differences and Similarities.

Google Play and Apple's App Store dominate the mobile health app market. We analyzed the metadata and descriptive texts of apps in the medical category using semi-automated retrospective app store analysis (SARASA) and compared the store offerings in terms of their number, descriptive texts, user ratings, medical device status, diseases, and conditions (both keyword-based). Relatively speaking, the store listings for the selected items were comparable.

Identifying Relevant FHIR Elements for Data Quality Assessment in the German Core Data Set.

The German Medical Informatics Initiative makes clinical routine data available for biomedical research. In total, 37 university hospitals have set up so-called data integration centers to facilitate this data reuse. A standardized set of HL7 FHIR profiles ("MII Core Data Set") defines the common data model across all centers.

Towards Prediction of Injuries in Traffic Accidents.

For people involved in road traffic accidents, the time necessary to respond is crucial and it is hard to discern, which persons in which cars most urgently need help. To plan the rescue operation before arriving at the scene, digital information regarding the severity of the accident is vital. Our framework aims to transmit available data from the in-car sensors and to simulate the forces enacted on occupants using injury models.

Data Sharing Platform for MIMIC-IV and MIMIC-ED Data Marts: Designing a Data Retrieving System Based on the Intra-Hospital Patient Transfer Pathway.

Accessibility to high-quality historical data for patients in hospitals may facilitate related predictive model development and data analysis experiments. This study provides a design for a data-sharing platform based on all possible criteria for Medical Information Mart for Intensive Care (MIMIC) IV and Emergency MIMIC-ED. Tables containing columns of medical attributions and outcomes were studied by a team of 5 experts in Medical Informatics.

Technological Assessment of Smart Wearables and 5G-Integrated Edge Computing for Real-Time Health Monitoring.

Smart wearables advance to reliably and continuously measure vital signs. Analyzing the produced data requires complex algorithms, which would unreasonably increase the energy consumption of mobile devices and exceed their computing power. Fifth-generation (5G) mobile networks provide low latencies, high bandwidth, and many connected devices and introduced multi-access edge computing, which brings high computation power close to the clients.

Usability Assessment as a Participatory Method for Implementing Technical Innovations in Nursing Care.

For the introduction of technical nursing care innovations, a usability assessment survey is conducted by nursing staff. The questionnaire is used before and after the introduction of technical products. This poster contribution shows the latest comparison of pre- and post-surveys on selected products.

Improving Emergency Service Quality and Patient Safety Through the Use of Cross-Sectoral Digital Feedback Systems - An Overview.

Background: Feedback is essential for personal and professional development, also in emergency services. However, EMS usually ends at the interface with the emergency department, thus, the long-term effect of initiated emergency measures often remains unclear for emergency personnel. Digital, data-driven tools providing systematic feedback on patients' outcome may be valuable to improve emergency service quality and patient safety.

Programming techniques for improving rule readability for rule-based information extraction natural language processing pipelines of unstructured and semi-structured medical texts.

Background: Extraction of medical terms and their corresponding values from semi-structured and unstructured texts of medical reports can be a time-consuming and error-prone process. Methods of natural language processing (NLP) can help define an extraction pipeline for accomplishing a structured format transformation strategy.

Objectives: In this paper, we build an NLP pipeline to extract values of the classification of malignant tumors (TNM) from unstructured and semi-structured pathology reports and import them further to a structured data source for a clinical study.

Lacking mechanistic disease definitions and corresponding association data hamper progress in network medicine and beyond.

A long-term objective of network medicine is to replace our current, mainly phenotype-based disease definitions by subtypes of health conditions corresponding to distinct pathomechanisms. For this, molecular and health data are modeled as networks and are mined for pathomechanisms. However, many such studies rely on large-scale disease association data where diseases are annotated using the very phenotype-based disease definitions the network medicine field aims to overcome.

A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms.

Background: This is a systematic review protocol to identify automated features, applied technologies, and algorithms in the electronic early warning/track and triage system (EW/TTS) developed to predict clinical deterioration (CD).

Methodology: This study will be conducted using PubMed, Scopus, and Web of Science databases to evaluate the features of EW/TTS in terms of their automated features, technologies, and algorithms. To this end, we will include any English articles reporting an EW/TTS without time limitation.

The effect of m-health applications on self-care improvement in older adults: A systematic review.

Participants: Four electronic databases were searched on March 6, 2020 including Scopus, PubMed, ISI, and Embase.

Methods: Our search consisted of concepts of "self-care," "elderly" and "Mobile device." English journal papers and, RCTs conducted for individuals older than 60 in the last 10 years were included.

Recognizing Human Activity of Daily Living Using a Flexible Wearable for 3D Spine Pose Tracking.

The World Health Organization recognizes physical activity as an influencing domain on quality of life. Monitoring, evaluating, and supervising it by wearable devices can contribute to the early detection and progress assessment of diseases such as Alzheimer's, rehabilitation, and exercises in telehealth, as well as abrupt events such as a fall. In this work, we use a non-invasive and non-intrusive flexible wearable device for 3D spine pose measurement to monitor and classify physical activity.

Orthopaedic and trauma surgeons' prioritisation of app quality principles based on their demographic background.

Background: Although apps are becoming increasingly relevant in healthcare, there is limited knowledge about how healthcare professionals perceive "quality" in this context and how quality principles that can aid them in assessing health-related apps may be prioritised. The objective was to investigate physicians' views of predefined (general) quality principles for health apps and to determine whether a ranking algorithm applied to the acquired data can provide stable results against various demographic influences and may thus be appropriate for prioritisation.

Methods: Participants of an online survey of members of two German professional orthopaedics associations conducted between 02/12/2019 and 02/01/2020 were asked about their perception of a set of quality principles for health apps (i.

Remote Monitoring of Colorectal Cancer Survivors Using a Smartphone App and Internet of Things-Based Device: Development and Usability Study.

Background: Patients with colorectal cancer who undergo surgery face many postoperative problems. These problems include the risk of relapse, side effects, and long-term complications.

Objective: This study sought to design and develop a remote monitoring system as a technological solution for the postdischarge care of these patients.

Research Data Management and Data Sharing for Reproducible Research-Results of a Community Survey of the German National Research Data Infrastructure Initiative Neuroscience.

Science is changing: the volume and complexity of data are increasing, the number of studies is growing and the goal of achieving reproducible results requires new solutions for scientific data management. In the field of neuroscience, the German National Research Data Infrastructure (NFDI-Neuro) initiative aims to develop sustainable solutions for research data management (RDM). To obtain an understanding of the present RDM situation in the neuroscience community, NFDI-Neuro conducted a comprehensive survey among the neuroscience community.

Trans-O-MIM-An International Research Project on Open Access Transformation: Outcomes and Lessons Learned.

Background: During the last decades, the Open Access paradigm has become an important approach for publishing new scientific knowledge. From 2015 to 2020, the Trans-O-MIM research project was undertaken with the intention to identify and to explore solutions in transforming subscription-based journals into Open Access journals. Trans-O-MIM stands for 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 with as an example.