scholarly journals Dealing with deepfakes – an interdisciplinary examination of the state of research and implications for communication studies

2021 ◽  
Vol 10 (1) ◽  
pp. 72-96
Author(s):  
Alexander Godulla ◽  
Christian P. Hoffmann ◽  
Daniel Seibert

Using artificial intelligence, it is becoming increasingly easy to create highly realistic but fake video content - so-called deepfakes. As a result, it is no longer possible always to distinguish real from mechanically created recordings with the naked eye. Despite the novelty of this phenomenon, regulators and industry players have started to address the risks associated with deepfakes. Yet research on deepfakes is still in its infancy. This paper presents findings from a systematic review of English-language deepfake research to identify salient discussions. We find that, to date, deepfake research is driven by computer science and law, with studies focusing on deepfake detection and regulation. While a number of studies address the potential of deepfakes for political disinformation, few have examined user perceptions of and reactions to deepfakes. Other notable research topics include challenges to journalistic practices and pornographic applications of deepfakes. We identify research gaps and derive implications for future communication studies research.

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Naseer Ahmed ◽  
Maria Shakoor Abbasi ◽  
Filza Zuberi ◽  
Warisha Qamar ◽  
Mohamad Syahrizal Bin Halim ◽  
...  

Objective. The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry. Materials and Methods. Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted. Results. The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics. Conclusion. The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Deborah Petrat

AbstractThe development of artificial intelligence (AI) technologies continues to advance. To fully exploit the potential, it is important to deal with the topics of human factors and ergonomics, so that a smooth implementation of AI applications can be realized. In order to map the current state of research in this area, three systematic literature reviews with different focuses were conducted. The seven observation levels of work processes according to Luczak and Volpert (1987) served as a basis. Overall n = 237 sources were found and analyzed. It can be seen that the research critically deals with human-centered, effective as well as efficient work in relation to AI. Research gaps, for example in the areas of corporate education concepts and participation and voice, identify further needs in research. The author postulates not to miss the transition between forecasts and verifiable facts.


2020 ◽  
Vol 48 (4) ◽  
pp. 225-236
Author(s):  
Xu Du ◽  
Juan Yang ◽  
Jui-Long Hung ◽  
Brett Shelton

Purpose Educational data mining (EDM) and learning analytics, which are highly related subjects but have different definitions and focuses, have enabled instructors to obtain a holistic view of student progress and trigger corresponding decision-making. Furthermore, the automation part of EDM is closer to the concept of artificial intelligence. Due to the wide applications of artificial intelligence in assorted fields, the authors are curious about the state-of-art of related applications in Education. Design/methodology/approach This study focused on systematically reviewing 1,219 EDM studies that were searched from five digital databases based on a strict search procedure. Although 33 reviews were attempted to synthesize research literature, several research gaps were identified. A comprehensive and systematic review report is needed to show us: what research trends can be revealed and what major research topics and open issues are existed in EDM research. Findings Results show that the EDM research has moved toward the early majority stage; EDM publications are mainly contributed by “actual analysis” category; machine learning or even deep learning algorithms have been widely adopted, but collecting actual larger data sets for EDM research is rare, especially in K-12. Four major research topics, including prediction of performance, decision support for teachers and learners, detection of behaviors and learner modeling and comparison or optimization of algorithms, have been identified. Some open issues and future research directions in EDM field are also put forward. Research limitations/implications Limitations for this search method include the likelihood of missing EDM research that was not captured through these portals. Originality/value This systematic review has not only reported the research trends of EDM but also discussed open issues to direct future research. Finally, it is concluded that the state-of-art of EDM research is far from the ideal of artificial intelligence and the automatic support part for teaching and learning in EDM may need improvement in the future work.


2020 ◽  
Author(s):  
Xia Jing

BACKGROUND Background: The unified medical language system (UMLS) has been a critical tool in biomedical and health informatics, and the year 2020 marks the 30th anniversary of UMLS. Despite its longevity, there is no systematic review on UMLS, in general. Thus, this systematic review was conducted to provide an overview of UMLS and its usage in English-language publications in the last 30 years. OBJECTIVE Objectives: The objective is twofold: to provide a comprehensive and systematic picture of the themes, their subtopics, and the publications under each category and to document systematic evidence of UMLS and how it has been used in English-language publications in the last 30 years. METHODS Methods: PubMed, ACM Digital Library, and Nursing & Allied Health Database were used to search for literature. The primary literature search strategy was as follows: UMLS was used as a MeSH term or a keyword or appeared in the title or abstract. Only English-language publications were considered. RESULTS Results: A total of 943 publications were included in the final analysis. After analysis and categorization of publications, UMLS was found to be used in the following emerging themes: natural language processing (NLP) (230 publications), information retrieval (125 publications), terminology study (90 publications), ontology and modeling (80 publications), medical subdomains (76 publications), other language studies (53 publications), artificial intelligence tools and applications (46 publications), patient care (35 publications), data mining and knowledge discovery (25 publications), medical education (20 publications), degree-related theses (13 publications), and digital library (5 publications) as well as UMLS itself (150 publications). CONCLUSIONS Conclusions: UMLS has been used and published successfully in patient care, medical education, digital libraries, and software development, as originally planned, as well as in degree-related theses, building artificial intelligence tools, data mining and knowledge discovery and more foundational work in methodology and middle layers that may lead to advanced products. NLP, UMLS itself, and information retrieval are the three themes with the most publications. The review provides systematic evidence of UMLS in English-language peer-reviewed publications in the last 30 years.


2020 ◽  
Author(s):  
Kurt D Shulver ◽  
Nicholas A Badcock

We report the results of a systematic review and meta-analysis investigating the relationship between perceptual anchoring and dyslexia. Our goal was to assess the direction and degree of effect between perceptual anchoring and reading ability in typical and atypical (dyslexic) readers. We performed a literature search of experiments explicitly assessing perceptual anchoring and reading ability using PsycInfo (Ovid, 1860 to 2020), MEDLINE (Ovid, 1860 to 2019), EMBASE (Ovid, 1883 to 2019), and PubMed for all available years up to June (2020). Our eligibility criteria consisted of English-language articles and, at minimum, one experimental group identified as dyslexic - either by reading assessment at the time, or by previous diagnosis. We assessed for risk of bias using an adapted version of the Newcastle-Ottawa scale. Six studies were included in this review, but only five (n = 280 participants) were included in the meta-analysis (we were unable to access the necessary data for one study).The overall effect was negative, large and statistically significant; g = -0.87, 95% CI [-1.47, 0.27]: a negative effect size indicating less perceptual anchoring in dyslexic versus non-dyslexic groups. Visual assessment of funnel plot and Egger’s test suggest minimal bias but with significant heterogeneity; Q (4) = 9.70, PI (prediction interval) [-2.32, -0.58]. The primary limitation of the current review is the small number of included studies. We discuss methodological limitations, such as limited power, and how future research may redress these concerns. The variability of effect sizes appears consistent with the inherent variability within subtypes of dyslexia. This level of dispersion seems indicative of the how we define cut-off thresholds between typical reading and dyslexia populations, but also the methodological tools we use to investigate individual performance.


2020 ◽  
Vol 16 ◽  
Author(s):  
Mariam Ahmed Saad ◽  
Mostafa Alfishawy ◽  
Mahmoud Nassar ◽  
Mahmoud Mohamed ◽  
Ignatius N Esene ◽  
...  

Introduction: Over 4.9 million cases of Coronavirus disease 2019 (COVID-19) have been confirmed since the worldwide pandemic began. Since the emergence of COVID-19, a number of confirmed cases reported autoimmune manifestations. Herein, we reviewed the reported COVID-19 cases with associated autoimmune manifestations. Methods: We searched PubMed database using all available keyword for COVID-19. All related studies between January 1st, 2020 to May 22nd, 2020 were reviewed. Only studies published in English language were considered. Articles were screened based on titles and abstract. All reports of confirmed COVID-19 patients who have associated clinical evidence of autoimmune disease were selected. Results: Among 10006 articles, searches yielded, Thirty-two relevant articles for full-text assessment. Twenty studies meet the eligibility criteria. The twenty eligible articles reported 33 cases of confirmed COVID-19 diagnosis who developed an autoimmune disease after the onset of covid-19 symptoms. Ages of patients varied from a 6 months old infant to 89 years old female (Mean=53.9 years of 28 cases); five cases had no information regarding their age. The time between symptoms of viral illness and onset of autoimmune symptoms ranged from 2 days to 33 days (Mean of the 33 cases=9.8 days). Autoimmune diseases were one case of subacute thyroiditis (3%), two cases of Kawasaki Disease (6.1%), three cases of coagulopathy and antiphospholipid syndrome (9.1%), three cases of immune thrombocytopenic purpura (9.1%), eight cases of autoimmune hemolytic anemia (24.2%), and sixteen cases of Guillain–Barré syndrome (48.5%). Conclusions: COVID-19 has been implicated in the development in a range of autoimmune diseases which may shed a light on the association between autoimmune diseases and infections.


2019 ◽  
Author(s):  
Sheeba Nadarajah ◽  
Susan Buchholz ◽  
Kristen Dickins

BACKGROUND Globally, cardiovascular disease is the leading cause of death. Cardiovascular mortality can be decreased by participation in cardiac rehabilitation. Researchers are exploring the use of mHealth technology in cardiac rehabilitation. OBJECTIVE The aim of this systematic review is to examine the effectiveness of randomized controlled trials that use a mHealth intervention as a part of an outpatient and/or home-based cardiac rehabilitation program on improving physical activity and physical fitness outcomes. METHODS For this systematic review, mHealth interventions were limited to text messaging, mobile apps, and use of a mobile phone network for data transmission, used to deliver cardiac rehabilitation program. Using six databases, the search strategy included published English language studies through 2016. Data was extracted independently by two reviewers, and then synthesized. RESULTS The initial search yielded 149 articles, of which 15 articles that represented nine studies met inclusion criteria. Articles were published from 2010 to 2016 and came from two continents. The majority (84%) of participants were male. Generally, the participant mean age was late 50s to early 60s. Text messaging was the most frequently used intervention. The results of the physical activity and physical fitness findings were mixed. Effect sizes for intervention as measured by the 6-minute walk test ranged from 0.46 to 0.58 and peak VO2 ranged from 0.03 to 1.35. CONCLUSIONS Globally, use of mHealth in outpatient and/or home-based cardiac rehabilitation is being studied with greater attention. However, these studies are limited by geography, gender, and age. Therefore, further research in the area of cardiac rehabilitation and mHealth is recommended, especially in developing countries, among women, and older adults.


Lupus ◽  
2020 ◽  
pp. 096120332096570
Author(s):  
Juliana P Ocanha-Xavier ◽  
Camila O Cola-Senra ◽  
Jose Candido C Xavier-Junior

Reticular erythematous mucinosis (REM) was first described 50 years ago, but only around 100 case reports in English have been published. Its relation with other inflammatory skin disorders is still being debated. We report a case of REM, including the clinical and histopathological findings. Also, a systematic review of 94 English-language reported cases is provided. The described criteria for clinical and histopathological diagnosis are highlighted in order to REM can be confidently diagnosed.


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