Improving performance in colorectal cancer histology decomposition using deep and ensemble machine learning.

In routine colorectal cancer management, histologic samples stained with hematoxylin and eosin are commonly used. Nonetheless, their potential for defining objective biomarkers for patient stratification and treatment selection is still being explored. The current gold standard relies on expensive and time-consuming genetic tests.

Virtual Reality Sickness Reduces Attention During Immersive Experiences.

In this paper, we show that Virtual Reality (VR) sickness is associated with a reduction in attention, which was detected with the P3b Event-Related Potential (ERP) component from electroencephalography (EEG) measurements collected in a dual-task paradigm. We hypothesized that sickness symptoms such as nausea, eyestrain, and fatigue would reduce the users' capacity to pay attention to tasks completed in a virtual environment, and that this reduction in attention would be dynamically reflected in a decrease of the P3b amplitude while VR sickness was experienced. In a user study, participants were taken on a tour through a museum in VR along paths with varying amounts of rotation, shown previously to cause different levels of VR sickness.

Improved accuracy in colorectal cancer tissue decomposition through refinement of established deep learning solutions.

Hematoxylin and eosin-stained biopsy slides are regularly available for colorectal cancer patients. These slides are often not used to define objective biomarkers for patient stratification and treatment selection. Standard biomarkers often pertain to costly and slow genetic tests.

Where am I? Location archetype keyword extraction from urban mobility patterns.

Can online behaviour be used as a proxy for studying urban mobility? The increasing availability of digital mobility traces has provided new insights into collective human behaviour. Mobility datasets have been shown to be an accurate proxy for daily behaviour and social patterns, and behavioural data from Twitter has been used to predict real world phenomena such as cinema ticket sale volumes, stock prices, and disease outbreaks. In this paper we correlate city-scale urban traffic patterns with online search trends to uncover keywords describing the pedestrian traffic location.

Multipurpose public displays: how shortcut menus affect usage.

Transitioning from bespoke, single-purpose public displays to generic, multipurpose ones entails a number of research challenges. One such challenge is understanding how to group and present available applications to users and what effect this grouping has on application use. This study of an iterative, longitudinal deployment of a multipurpose public display examines two mechanisms that help users find the available applications: a quick-launch menu and a browsable application directory.