AI ethics in May 2018

BACKGROUND: Core collections provide genebank curators and plant breeders a way to reduce size of their collections and populations, while minimizing impact on genetic diversity and allele frequency. Many methods have been proposed to generate core collections, often using distance metrics to quantify the similarity of two accessions, based on genetic marker data or phenotypic traits. Core Hunter is a multi-purpose core subset selection tool that uses local search algorithms to generate subsets

BACKGROUND: Alzheimer's Disease (AD) is a neurodegenaritive disorder characterized by a progressive dementia, for which actually no cure is known. An early detection of patients affected by AD can be obtained by analyzing their electroencephalography (EEG) signals, which show a reduction of the complexity, a perturbation of the synchrony, and a slowing down of the rhythms. METHODS: In this work, we apply a procedure that exploits feature extraction and classification techniques to EEG signals, w

Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detection. However, CNNs are typically only tenable with relatively small image sizes (200 × 200 pixels). Only recently, Fully convolutional networks (FCN) a

It seems obvious that phenomenally conscious experience is something of great value, and that this value maps onto a range of important ethical issues. For example, claims about the value of life for those in Permanent Vegetative State (PVS); debates about treatment and study of disorders of consciousness; controversies about end-of-life care for those with advanced dementia; and arguments about the moral status of embryos, fetuses, and non-human animals arguably turn on the moral significance o

Systematic reviews (SR) are vital to health care, but have become complicated and time-consuming, due to the rapid expansion of evidence to be synthesised. Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. Automation tools need

Reviewing recent research on poverty in the United States, we derive a conceptual framework with three main characteristics. First, poverty is multidimensional, compounding material hardship with human frailty, generational trauma, family and neighborhood violence, and broken institutions. Second, poverty is relational, produced through connections between the truly advantaged and the truly disadvantaged. Third, a component of this conceptual framework is transparently normative, applying empiri

This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain-computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized that, contrary to the popular trend of focusing mostly on the machine learning aspects of MI BCI training, a comprehensive mutual learning methodology that reinstates the three learning pillars (at the machine, subject, and application level) as equa

The 2030 Agenda for Sustainable Development covers a wide range of interrelated goals, including poverty eradication and economic growth, social inclusion, environmental sustainability and peace for all people by 2030. Policy decisions to meet the Sustainable Development Goals (SDGs) need to be informed by policy-relevant evidence co-designed and co-produced with the pertinent stakeholders, taking into consideration local and political contexts. Universities are uniquely placed to lead the cross

Background: Frequent expression of negative emotion words on social media has been linked to depression. However, metrics have relied on average values, not dynamic measures of emotional volatility. Objective: The aim of this study was to report on the associations between depression severity and the variability (time-unstructured) and instability (time-structured) in emotion word expression on Facebook and Twitter across status updates. Methods: Status updates and depression severity ratings of

Ideas and Opinions3 July 2018Physician Burnout in the Electronic Health Record Era: Are We Ignoring the Real Cause?N. Lance Downing, MD, David W. Bates, MD, MSc, and Christopher A. Longhurst, MD, MSN. Lance Downing, MDStanford University School of Medicine, Stanford, California (N.L.D.)Search for more papers by this author, David W. Bates, MD, MScBrigham and Women's Hospital, Harvard Medical School, and Harvard School of Public Health, Boston, Massachusetts (D.W.B.)Search for more papers by this

Building on new developments in the psychology of working framework (PWF) and psychology of working theory (PWT), this article proposes a rationale and research agenda for applied psychologists and career development professionals to contribute to the many challenges related to human rights and decent work. Recent and ongoing changes in the world are contributing to a significant loss of decent work, including a rise of unemployment, underemployment, and precarious work across the globe. By fail

BACKGROUND: The emergence of robotics is transforming industries around the world. Robot technologies are evolving exponentially, particularly as they converge with other functionalities such as artificial intelligence to learn from their environment, from each other, and from humans. OBJECTIVE: The goal of the research was to understand the emerging role of robotics in health care and identify existing and likely future challenges to maximize the benefits associated with robotics and related co

Research into suicide prevention has been hampered by methodological limitations such as low sample size and recall bias. Recently, Natural Language Processing (NLP) strategies have been used with Electronic Health Records to increase information extraction from free text notes as well as structured fields concerning suicidality and this allows access to much larger cohorts than previously possible. This paper presents two novel NLP approaches - a rule-based approach to classify the presence of

Emotional Intelligence (EI) has been an important and controversial topic during the last few decades. Its significance and its correlation with many domains of life has made it the subject of expert study. EI is the rudder for feeling, thinking, learning, problem-solving, and decision-making. In this article, we present an emotional⁻cognitive based approach to the process of gaining emotional intelligence and thus, we suggest a nine-layer pyramid of emotional intelligence and the gradual develo

BACKGROUND: Sequence data used in reconstructing phylogenetic trees may include various sources of error. Typically errors are detected at the sequence level, but when missed, the erroneous sequences often appear as unexpectedly long branches in the inferred phylogeny. RESULTS: We propose an automatic method to detect such errors. We build a phylogeny including all the data then detect sequences that artificially inflate the tree diameter. We formulate an optimization problem, called the k-shrin

Emerging combinations of artificial intelligence, big data, and the applications these enable are receiving significant media and policy attention. Much of the attention concerns privacy and other ethical issues. In our article, we suggest that what is needed now is a way to comprehensively understand these issues and find mechanisms of addressing them that involve stakeholders, including civil society, to ensure that these technologies' benefits outweigh their disadvantages. We suggest that the

Medical students are exposed to multiple factors during their academic and clinical study that have been shown to contribute to high levels of depression, anxiety, and stress. The purpose of this article was to explore the issue of depression in the medical student population, including prevalence, causes, and key issues, along with suggestions for early identification and support from one medical school in New Zealand. After establishing that the prevalence of depression is higher for medical s

Although different types of teams increasingly employ embodied physical action (EPA) robots as a collaborative technology to accomplish their work, we know very little about what makes such teams successful. This paper has two objectives: the first is to examine whether a team’s emotional attachment to its robots can lead to better team performance and viability; the second is to determine whether robot and team identification can promote a team’s emotional attachment to its robots. To achieve t