AI ethics in April 2020

BACKGROUND: To explore and describe the current literature surrounding bacterial/fungal coinfection in patients with coronavirus infection. METHODS: MEDLINE, EMBASE, and Web of Science were searched using broad-based search criteria relating to coronavirus and bacterial coinfection. Articles presenting clinical data for patients with coronavirus infection (defined as SARS-1, MERS, SARS-CoV-2, and other coronavirus) and bacterial/fungal coinfection reported in English, Mandarin, or Italian were i

The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present MINIMAR (MINimum Infor

The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is r

•Baricitinib at 4 mg/day/orally was given to 12 patients with moderate COVID-19.•In baricitinib-treated patients no adverse events were recorded, after 2 weeks.•Clinical and respiratory parameters significantly improved at 2 weeks.•None of the baricitinib-treated patients required admission to ICU.•Proper control group was missing; this is required to demonstrate the efficacy. As discussed in the Journal recently1Li R. Qiao S. Zhang G Analysis of angiotensin-converting enzyme 2 (ACE2) from diffe

The number of academic papers in the area of Artificial Intelligence (AI) and its applications across business and management domains has risen significantly in the last decade, and that rise has been followed by an increase in the number of systematic literature reviews. The aim of this study is to provide an overview of existing systematic reviews in this growing area of research and to synthesise their findings related to enablers, barriers and social implications of the AI adoption in busine

The term "artificial intelligence" (AI) refers to the idea of machines being capable of performing human tasks. A subdomain of AI is machine learning (ML), which "learns" intrinsic statistical patterns in data to eventually cast predictions on unseen data. Deep learning is a ML technique using multi-layer mathematical operations for learning and inferring on complex data like imagery. This succinct narrative review describes the application, limitations and possible future of AI-based dental dia

Artificial Intelligence (AI) plays an increasingly important role in improving HCI and user experience. Yet many challenges persist in designing and innovating valuable human-AI interactions. For example, AI systems can make unpredictable errors, and these errors damage UX and even lead to undesired societal impact. However, HCI routinely grapples with complex technologies and mitigates their unintended consequences. What makes AI different? What makes human-AI interaction appear particularly di

Many organizations have published principles intended to guide the ethical development and deployment of AI systems; however, their abstract nature makes them difficult to operationalize. Some organizations have therefore produced AI ethics checklists, as well as checklists for more specific concepts, such as fairness, as applied to AI systems. But unless checklists are grounded in practitioners' needs, they may be misused. To understand the role of checklists in AI ethics, we conducted an itera

BACKGROUND At the end of 2019, the COVID-19 outbreak began in Wuhan, Hubei, China, and spread rapidly to the whole country within 1 month. This new epidemic caused a great mental reaction among the public. This study aimed to assess and compare the prevalence and associated factors of anxiety and depression among the public affected by quarantine and those unaffected during the COVID-19 outbreak in southwestern China in early Feb. 2020. MATERIAL AND METHODS Data were collected using the self-rat

This paper examines the political economy of artificial intelligence (AI) and education in China, through an analysis of government policy and private sector enterprise. While media and policy discourse often portray China’s AI development in terms of a unified national strategy, and a burgeoning geopolitical contestation for future global dominance, this analysis will suggest a more nuanced internal complexity, involving differing regional networks and international corporate activity. The firs

Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, a

Over the past several years, many healthcare applications have been developed to enhancethe healthcare industry. Recent advancements in information technology and blockchain technologyhave revolutionized electronic healthcare research and industry. The innovation of miniaturizedhealthcare sensors for monitoring patient vital signs has improved and secured the human healthcaresystem. The increase in portable health devices has enhanced the quality of health-monitoringstatus both at an activity/fi

Abstract This survey investigates current techniques for representing qualitative data for use as input to neural networks. Techniques for using qualitative data in neural networks are well known. However, researchers continue to discover new variations or entirely new methods for working with categorical data in neural networks. Our primary contribution is to cover these representation techniques in a single work. Practitioners working with big data often have a need to encode categorical value

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Netwo

© Academy of Management Annals. People design and use technology for work. In return, technology shapes work and people. As information communication technology (ICT) becomes ever more embedded in today’s increasingly digital organizations, the nature of our jobs and employees’ work experiences are strongly affected by ICT use. This cross-disciplinary review focuses on work design as a central explanatory vehicle for exploring how individual ICT usage influences employees’ effectiveness and well

The idea of artificial intelligence for social good (henceforth AI4SG) is gaining traction within information societies in general and the AI community in particular. It has the potential to tackle social problems through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies. This article addresses this gap by identifying s

The significant changes which have occurred in the competitive scenario in which fashion companies operate, combined with deep transformation in the lifestyles of final consumers, translate into the need to redefine the business models. Starting from a general overview of the emerging trends today affecting the fashion industry, the paper will devote particular attention to the analysis of the most important phenomena that are influencing this market and the drivers for long-lasting competitiven

Artificial intelligence (AI) is a powerful concept still in its infancy that has the potential, if utilised responsibly, to provide a vehicle for positive change that could promote sustainable transitions to a more resource-efficient livability paradigm. AI with its deep learning functions and capabilities can be employed as a tool which empowers machines to solve problems that could reform urban landscapes as we have known them for decades now and help with establishing a new era; the era of th

The development of digital pathology and progression of state-of-the-art algorithms for computer vision have led to increasing interest in the use of artificial intelligence (AI), especially deep learning (DL)-based AI, in tumor pathology. The DL-based algorithms have been developed to conduct all kinds of work involved in tumor pathology, including tumor diagnosis, subtyping, grading, staging, and prognostic prediction, as well as the identification of pathological features, biomarkers and gene

Abstract Multinational enterprise (MNE) subsidiaries abroad are important organizations in their own rights. They typically hold some of the MNE’s most critical resources, and operate at the forefront of complex international environments. In this review, we identify and organize theoretical and empirical research on subsidiary management based on over 600 articles in leading academic journals. We develop a conceptual framework that integrates complementary streams of theoretical and empirical r