Triptychon: Usability evaluation and implementation of a web-based application for patients' lab and vital parameters.

Background: A major challenge in healthcare is the interpretation of the constantly increasing amount of clinical data of interest to inpatients for diagnosis and therapy. It is vital to accurately structure and represent data from different sources to help clinicians make informed decisions.

Objective: We evaluated the usability of our tool 'Triptychon' - a three-part visualisation dashboard of essential patients' medical data provided by a direct overview of their hospitalisation information, laboratory, and vital parameters over time.

Visualization Techniques of Time-Oriented Data for the Comparison of Single Patients With Multiple Patients or Cohorts: Scoping Review.

Background: Visual analysis and data delivery in the form of visualizations are of great importance in health care, as such forms of presentation can reduce errors and improve care and can also help provide new insights into long-term disease progression. Information visualization and visual analytics also address the complexity of long-term, time-oriented patient data by reducing inherent complexity and facilitating a focus on underlying and hidden patterns.

Objective: This review aims to provide an overview of visualization techniques for time-oriented data in health care, supporting the comparison of patients.

Transfer learning for medical image classification: a literature review.

Background: Transfer learning (TL) with convolutional neural networks aims to improve performances on a new task by leveraging the knowledge of similar tasks learned in advance. It has made a major contribution to medical image analysis as it overcomes the data scarcity problem as well as it saves time and hardware resources. However, transfer learning has been arbitrarily configured in the majority of studies.

SARS-CoV-2 Antibody Testing - How to Increase the Positive Predictive Value.

Background: Despite increasing COVID-19 infection rates, low overall prevalence resulting in a poor positive predictive value (PPV) of serological tests requires strategies to increase specificity. We therefore investigated a dual diagnostic strategy and evaluated the correlation between the severity of a SARS-CoV-2 infection and the detectable immune-response.

Methods: Participants were systematically categorized into positive and control cohorts and a probability score of COVID-19 was calculated based on clinical symptoms.

[Evaluation of a SARS-CoV-2 test strategy in a southwestern university hospital at the beginning of the COVID-19 pandemic].

Background: At the beginning of the COVID-19 pandemic, the German Robert Koch Institute (RKI) published several guidelines addressing the medical health services helping to detect SARS CoV‑2. Needing an available and specific test strategy regarding SARS-CoV‑2, our own test strategy strictly followed these testing criteria.

Materials And Methods: Using a retrospective analysis, we verified if such a test strategy was an effective tool in the context of infection prevention control and as reliable SARS-CoV‑2 detection.

Tracking stem cell differentiation in the setting of automated optogenetic stimulation.

Membrane depolarization has been shown to play an important role in the neural differentiation of stem cells and in the survival and function of mature neurons. Here, we introduce a microbial opsin into ESCs and develop optogenetic technology for stem cell engineering applications, with an automated system for noninvasive modulation of ESC differentiation employing fast optogenetic control of ion flux. Mouse ESCs were stably transduced with channelrhodopsin-2 (ChR2)-yellow fluorescent protein and purified by fluorescence activated cell sorting (FACS).