AI ethics in May 2019

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. In the last decade, studies on AD diagnosis has attached great significance to artificial intelligence-based diagnostic algorithms. Among the diverse modalities of imaging data, T1-weighted MR and FDG-PET are widely used for this task. In this paper, we propose a convolutional neural network (CNN) to integrate all the multi-modality information included in both T1-MR and FDG-PET images of the hippocampal area, for the

The processes underwriting the acquisition of culture remain unclear. How are shared habits, norms, and expectations learned and maintained with precision and reliability across large-scale sociocultural ensembles? Is there a unifying account of the mechanisms involved in the acquisition of culture? Notions such as "shared expectations," the "selective patterning of attention and behaviour," "cultural evolution," "cultural inheritance," and "implicit learning" are the main candidates to underpin

Blended Learning (BL) creates a ‘rich’ educational environment with multiple technology-enabled communication forms in both face-to-face and online teaching. Students’ characteristics are closely related to the learning effectiveness in the BL environment. Students’ ability to direct themselves in learning and to utilise learning technologies can affect student learning effectiveness. This study examined the impacts of self-directed learning, technology readiness, and learning motivation on the

BACKGROUND: Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-optimal performance across all patient groups. Data-driven techniques based on machine learning (ML) might improve the performance of risk predictions by agnostically discovering novel risk predictors and learning the complex interactions between them.

The Government of Japan’s “Society 5.0” initiative aims to create a cyber-physical society in which (among other things) citizens’ daily lives will be enhanced through increasingly close collaboration with artificially intelligent systems. However, an apparent paradox lies at the heart of efforts to create a more “human-centered” society in which human beings will live alongside a proliferating array of increasingly autonomous social robots and embodied AI. This study seeks to investigate the pr

The absence of legal and regulatory frameworks around the collection, sharing and use of agricultural data contributes to the range of challenges currently being faced by farmers considering adoption of smart farming technologies. Many laws potentially influence the ownership, control of and access to data, in this paper we examine the attitudes of farmers to the collection, control, sharing and use of their farm data. Australian agriculture and the attitudes of Australian farmers to the adoptio

The Cox proportional hazards model commonly used to evaluate prognostic variables in survival of cancer patients may be too simplistic to properly predict a cancer patient's outcome since it assumes that the outcome is a linear combination of covariates. In this retrospective study including 255 patients suitable for analysis who underwent surgical treatment in our department from 2000 to 2017, we applied a deep learning-based survival prediction method in oral squamous cell carcinoma (SCC) pati

Technological advances have made possible industrial and commercial applications of artificial intelligence, virtual reality and highly integrated manufacturing systems. It has also freed business activity from a focus on place, as both work activities and markets have been able to harness information and communication technologies in order to operate remotely. As a result, researchers have highlighted a phenomenon of ‘smart’ working. Some have pointed to a fourth Industrial Revolution (Industry

This editorial draws attention to time to advance entrepreneurship research by focusing on two aspects of time—time perspective and time management. We initiate a deeper conversation on time in entrepreneurship and illustrate the value of a time-based lens for entrepreneurship research through discussing examples at the individual, firm and context levels. These examples consider underdog and portfolio entrepreneurs; well-being; social and unethical entrepreneurial behavior; entrepreneurial team

We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor—the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, auto

Taiwan's National Health Insurance Research Database (NHIRD) exemplifies a population-level data source for generating real-world evidence to support clinical decisions and health care policy-making. Like with all claims databases, there have been some validity concerns of studies using the NHIRD, such as the accuracy of diagnosis codes and issues around unmeasured confounders. Endeavors to validate diagnosed codes or to develop methodologic approaches to address unmeasured confounders have larg

Increasingly, management researchers are using topic modeling, a new method borrowed from computer science, to reveal phenomenon-based constructs and grounded conceptual relationships in textual data. By conceptualizing topic modeling as the process of rendering constructs and conceptual relationships from textual data, we demonstrate how this new method can advance management scholarship without turning topic modeling into a black box of complex computer-driven algorithms. We begin by comparing