Use of prognostic gene expression profiling tests in primary breast cancer treatment: a German real-world patient survey.

In primary breast cancer, gene expression profiling tests can support adjuvant chemotherapy treatment decisions. Real-world test use in Germany was investigated in an online survey of female breast cancer patients (n = 475). Relationships between three groups were examined for clinical and statistical relevance: no test indication (n = 353), test indication and tested (n = 65), and test indication but not tested (n = 57).

[PHARAO study: drug treatment of inflammatory rheumatic diseases : Guideline-conform treatment with biologics follows availability of biosimilars].

Background: With the introduction of tumor necrosis factor (TNF) alpha inhibitors, the treatment of inflammatory rheumatic diseases (IRD) has undergone a fundamental change. Several of the originally high-priced biologics are now accessible as lower cost biosimilars, removing a significant impediment to prescription.

Objective: The present study investigated whether the availability of biosimilars is associated with an improvement in the care of IRD.

Low-Cost Multispectral System Design for Pigment Analysis in Works of Art.

To better understand and preserve works of art, knowledge is needed about the pigments used to create the artwork. Various noninvasive techniques have been used previously to create pigment maps, such as combining X-ray fluorescence and hyperspectral imaging data. Unfortunately, most museums have limited funding for the expense of specialized research equipment, such as hyperspectral reflectance imaging systems.

Leveraging expert feature knowledge for predicting image aesthetics.

The ability to rank images based on their appearance finds many real-world applications such as image retrieval or image album creation. Despite the recent dominance of deep learning methods in computer vision which often result in superior performance, they are not always the methods of choice because they lack interpretability. In this work, we investigate the possibility of improving image aesthetic inference of convolutional neural networks with hand-designed features that rely on domain expertise in various fields.