AI ethics in March 2017

BACKGROUND: Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well

The article explores the coloniality of knowledge production in comparative education in and about (post)socialist spaces of southeast/central Europe and the former Soviet Union after the Cold War. We engage in a particular form of decoloniality, or what Walter Mignolo terms “delinking,” to fracture the hegemony of Western-centric knowledge and enable comparative education to gain a global viewpoint that is more inclusive of different voices. Our critique is threefold. First, we engage in rethin

The integration of digital technologies at institutions of higher education are profoundly influencing formal learning on a global scale. Social-constructivist models of fully online learning are well-positioned to address the demands of government, and economic and social-development organizations for civically-engaged individuals with strong problem-solving, critical-thinking and collaboration competencies. With an established record of performance at the University of Ontario Institute of Tec

Topological networks lie at the heart of our cities and social milieu. However, it remains unclear how and when the brain processes topological structures to guide future behaviour during everyday life. Using fMRI in humans and a simulation of London (UK), here we show that, specifically when new streets are entered during navigation of the city, right posterior hippocampal activity indexes the change in the number of local topological connections available for future travel and right anterior h

The "14-day rule" for embryo research stipulates that experiments with intact human embryos must not allow them to develop beyond 14 days or the appearance of the primitive streak. However, recent experiments showing that suitably cultured human pluripotent stem cells can self-organize and recapitulate embryonic features have highlighted difficulties with the 14-day rule and led to calls for its reassessment. Here we argue that these and related experiments raise more foundational issues that ca

Slit-lamp images play an essential role for diagnosis of pediatric cataracts. We present a computer vision-based framework for the automatic localization and diagnosis of slit-lamp images by identifying the lens region of interest (ROI) and employing a deep learning convolutional neural network (CNN). First, three grading degrees for slit-lamp images are proposed in conjunction with three leading ophthalmologists. The lens ROI is located in an automated manner in the original image using two suc

Data-driven tools and techniques, particularly machine learning methods that underpin artificial intelligence, offer promise in improving healthcare systems and services. One of the companies aspiring to pioneer these advances is DeepMind Technologies Limited, a wholly-owned subsidiary of the Google conglomerate, Alphabet Inc. In 2016, DeepMind announced its first major health project: a collaboration with the Royal Free London NHS Foundation Trust, to assist in the management of acute kidney in

The availability of smartphone and wearable sensor technology is leading to a rapid accumulation of human subject data, and machine learning is emerging as a technique to map those data into clinical predictions. As machine learning algorithms are increasingly used to support clinical decision making, it is vital to reliably quantify their prediction accuracy. Cross-validation (CV) is the standard approach where the accuracy of such algorithms is evaluated on part of the data the algorithm has n

Impaired procedural learning has been suggested as a possible cause of developmental dyslexia (DD) and specific language impairment (SLI). This study examined the relationship between measures of verbal and non-verbal implicit and explicit learning and measures of language, literacy and arithmetic attainment in a large sample of 7 to 8-year-old children. Measures of verbal explicit learning were correlated with measures of attainment. In contrast, no relationships between measures of implicit le

Autism spectrum disorder (ASD) and Attention-deficit/hyperactivity disorder (ADHD) are often comorbid. The purpose of this study is to explore the relationships between ASD and ADHD symptoms by applying causal modeling. We used a large phenotypic data set of 417 children with ASD and/or ADHD, 562 affected and unaffected siblings, and 414 controls, to infer a structural equation model using a causal discovery algorithm. Three distinct pathways between ASD and ADHD were identified: (1) from impuls

The Portuguese population enjoys good health and increasing life expectancy, though at lower levels than other western European countries. All residents in Portugal have access to health care provided by the National Health Service (NHS), financed mainly through taxation. Co-payments have been increasing over time, and the level of cost-sharing is highest for pharmaceutical products. Approximately one-fifth to a quarter of the population enjoys a second (or more) layer of health insurance covera