AI ethics in August 2017

<ns4:p> <ns4:bold>Background</ns4:bold> : “Open peer review” (OPR), despite being a major pillar of Open Science, has neither a standardized definition nor an agreed schema of its features and implementations. The literature reflects this, with numerous overlapping and contradictory definitions. While for some the term refers to peer review where the identities of both author and reviewer are disclosed to each other, for others it signifies systems where reviewer reports are published alongside

BACKGROUND: Target identification and validation is a pressing challenge in the pharmaceutical industry, with many of the programmes that fail for efficacy reasons showing poor association between the drug target and the disease. Computational prediction of successful targets could have a considerable impact on attrition rates in the drug discovery pipeline by significantly reducing the initial search space. Here, we explore whether gene-disease association data from the Open Targets platform is

Gaze following occurs automatically in social interactions, but the degree to which gaze is followed depends on whether an agent is perceived to have a mind, making its behavior socially more relevant for the interaction. Mind perception also modulates the attitudes we have toward others, and determines the degree of empathy, prosociality, and morality invested in social interactions. Seeing mind in others is not exclusive to human agents, but mind can also be ascribed to non-human agents like r

Rhegmatogenous retinal detachment (RRD) is a serious condition that can lead to blindness; however, it is highly treatable with timely and appropriate treatment. Thus, early diagnosis and treatment of RRD is crucial. In this study, we applied deep learning, a machine-learning technology, to detect RRD using ultra-wide-field fundus images and investigated its performance. In total, 411 images (329 for training and 82 for grading) from 407 RRD patients and 420 images (336 for training and 84 for g

This paper presents the results from the application of a serious game called Stigma-Stop among a group of high school students with the aim of reducing the stigma toward mental illnesses. The video game features characters with various mental disorders (schizophrenia, depression, bipolar disorder, and panic disorder with agoraphobia) and provides information about these problems. Additionally, the game asks players about whether they have ever felt the same as the characters, if they believe th

Blockchain has drawn attention as the next-generation financial technology due to its security that suits the informatization era. In particular, it provides security through the authentication of peers that share virtual cash, encryption, and the generation of hash value. According to the global financial industry, the market for security-based blockchain technology is expected to grow to about USD 20 billion by 2020. In addition, blockchain can be applied beyond the Internet of Things (IoT) en

Fog computing is a new paradigm that extends the Cloud platform model by providing computing resources on the edges of a network. It can be described as a cloud-like platform having similar data, computation, storage and application services, but is fundamentally different in that it is decentralized. In addition, Fog systems are capable of processing large amounts of data locally, operate on-premise, are fully portable, and can be installed on heterogeneous hardware. These features make the Fog

Abstract Discourse about smart algorithms and digital social agents still refers primarily to the construction of artificial intelligence that reproduces the faculties of individuals. Recent developments, however, show that algorithms are more efficient when they abandon this goal and try instead to reproduce the ability to communicate. Algorithms that do not “think” like people can affect the ability to obtain and process information in society. Referring to the concept of communication in Nikl

The increase of publicly available bioactivity data in recent years has fueled and catalyzed research in chemogenomics, data mining, and modeling approaches. As a direct result, over the past few years a multitude of different methods have been reported and evaluated, such as target fishing, nearest neighbor similarity-based methods, and Quantitative Structure Activity Relationship (QSAR)-based protocols. However, such studies are typically conducted on different datasets, using different valida

BACKGROUND: Currently, the typically adopted hand prosthesis surface electromyography (sEMG) control strategies do not provide the users with a natural control feeling and do not exploit all the potential of commercially available multi-fingered hand prostheses. Pattern recognition and machine learning techniques applied to sEMG can be effective for a natural control based on the residual muscles contraction of amputated people corresponding to phantom limb movements. As the researches has reach

Despite the ubiquity of textual data, so far few researchers have applied text mining to answer organizational research questions. Text mining, which essentially entails a quantitative approach to the analysis of (usually) voluminous textual data, helps accelerate knowledge discovery by radically increasing the amount data that can be analyzed. This article aims to acquaint organizational researchers with the fundamental logic underpinning text mining, the analytical stages involved, and contemp

Aims: Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research. Methods and results: We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidabl

A primary goal of polygenic scores, which aggregate the effects of thousands of trait-associated DNA variants discovered in genome-wide association studies (GWASs), is to estimate individual-specific genetic propensities and predict outcomes. This is typically achieved using a single polygenic score, but here we use a multi-polygenic score (MPS) approach to increase predictive power by exploiting the joint power of multiple discovery GWASs, without assumptions about the relationships among predi

Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer's disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44). Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education) and better maintenance of memory in mild cognitive impairment (MCI). Since the LFC is a hub of th

In this paper we introduce a novel dataset, the Multimodal Human-Human-Robot-Interactions (MHHRI) dataset, with the aim of studying personality simultaneously in human-human interactions (HHI) and human-robot interactions (HRI) and its relationship with engagement. Multimodal data was collected during a controlled interaction study where dyadic interactions between two human participants and triadic interactions between two human participants and a robot took place with interactants asking a set

AIMS: Evaluating expression of the human epidermal growth factor receptor 2 (HER2) by visual examination of immunohistochemistry (IHC) on invasive breast cancer (BCa) is a key part of the diagnostic assessment of BCa due to its recognized importance as a predictive and prognostic marker in clinical practice. However, visual scoring of HER2 is subjective, and consequently prone to interobserver variability. Given the prognostic and therapeutic implications of HER2 scoring, a more objective method

OBJECTIVES: To test the effects of individual, nonfacilitated sessions with PARO (version 9), when compared against a look-alike plush toy and usual care, on the emotional and behavioral symptoms of dementia for people living in long-term care facilities. DESIGN: Parallel, 3-group, cluster-randomized controlled trial conducted between June 14, 2014, and May 16, 2015. SETTING: Twenty-eight long-term care facilities operated by 20 care organizations located in South-East Queensland, Australia. PAR

In recent years, there has been widespread excitement around the potential for technology to transform learning. As investments in education technology continue to grow, students, parents, and teachers face a seemingly endless array of education technologies from which to choosefrom digital personalized learning platforms to educational games to online courses. Amidst the excitement, it is important to step back and understand how technology can help-or in some cases hinder-how students learn. T

Extremely brachycephalic, or short-muzzled, dog breeds such as pugs, French bulldogs, and bulldogs are prone to the conformation-related respiratory disorder-brachycephalic obstructive airway syndrome (BOAS). Affected dogs present with a wide range of clinical signs from snoring and exercise intolerance, to life-threatening events such as syncope. In this study, conformational risk factors for BOAS that could potentially aid in breeding away from BOAS were sought. Six hundred and four pugs, Fren