The scarcity of labeled data often limits the application of supervised deep learning
techniques for medical image segmentation. This has motivated the development of semi-supervised …

Recent studies have shown a worrying decline in the quantity and diversity of insects at a
number of locations in Europe (Hallmann et al. 2017) and elsewhere (Lister and Garcia 2018). …

The potential of citizen scientists to contribute to information about occurrences of species and
other biodiversity questions is large because of the ubiquitous presence of organisms and …

Volunteers, researchers and citizen scientists are important contributors to observation and
monitoring databases. Their contributions thus become part of a global digital data pool, that …

Objective To determine the sensitivity and specificity of a Computer Aided Diagnosis (CAD)
program for scoring chest x-rays (CXRs) of presumptive tuberculosis (TB) patients compared …

Adversarial attacks are considered a potentially serious security threat for machine learning
systems. Medical image analysis (MedIA) systems have recently been argued to be …

Chest radiographs are the most common exam in radiology. They are essential for the
management of various diseases associated with high mortality and morbidity and display a wide …

Automatic detection of tuberculosis (TB) on chest radiographs is a difficult problem because
of the diverse presentation of the disease. A combination of detection systems for …

SETTING: A busy urban health centre in Lusaka, Zambia.OBJECTIVE: To compare the
accuracy of automated reading (CAD4TB) with the interpretation of digital chest radiograph (CXR) …

Tuberculosis (TB) is a common disease with high mortality and morbidity rates worldwide.
Automatic systems to detect TB on chest radiographs (CXRs) can improve the efficiency of …