Data-centric AI approach for automated wildflower monitoring.

We present the Eindhoven Wildflower Dataset (EWD) as well as a PyTorch object detection model that is able to classify and count wildflowers. EWD, collected over two entire flowering seasons and expert annotated, contains 2,002 top-view images of flowering plants captured 'in the wild' in five different landscape types (roadsides, urban green spaces, cropland, weed-rich grassland, marshland). It holds a total of 65,571 annotations for 160 species belonging to 31 different families of flowering plants and serves as a reference dataset for automating wildflower monitoring and object detection in general.

Wearables measuring electrodermal activity to assess perceived stress in care: a scoping review.

Background: Chronic stress responses can lead to physical and behavioural health problems, often experienced and observed in the care of people with intellectual disabilities or people with dementia. Electrodermal activity (EDA) is a bio-signal for stress, which can be measured by wearables and thereby support stress management. However, the how, when and to what extent patients and healthcare providers can benefit is unclear.

A new method of real-time skin dose visualization. Clinical evaluation of fluoroscopically guided interventions.

Introduction: We have conducted a prospective study to clinically evaluate a new radiation dose observing tool that displays patient's peak skin dose (PSD) map in real time.

Methods: The skin dose map (SDM) prototype quantifies the air kerma based on exposure parameters from the X-ray system. The accuracy of this prototype was evaluated with radiochromic films, which were used as a mean for PSD measurement.