Virtual reality (VR) and augmented reality (AR) have recently become popular research themes. However, there are no published bibliometric reports that have analyzed the corresponding scientific ...literature in relation to the application of these technologies in medicine.
We used a bibliometric approach to identify and analyze the scientific literature on VR and AR research in medicine, revealing the popular research topics, key authors, scientific institutions, countries, and journals. We further aimed to capture and describe the themes and medical conditions most commonly investigated by VR and AR research.
The Web of Science electronic database was searched to identify relevant papers on VR research in medicine. Basic publication and citation data were acquired using the "Analyze" and "Create Citation Report" functions of the database. Complete bibliographic data were exported to VOSviewer and Bibliometrix, dedicated bibliometric software packages, for further analyses. Visualization maps were generated to illustrate the recurring keywords and words mentioned in the titles and abstracts.
The analysis was based on data from 8399 papers. Major research themes were diagnostic and surgical procedures, as well as rehabilitation. Commonly studied medical conditions were pain, stroke, anxiety, depression, fear, cancer, and neurodegenerative disorders. Overall, contributions to the literature were globally distributed with heaviest contributions from the United States and United Kingdom. Studies from more clinically related research areas such as surgery, psychology, neurosciences, and rehabilitation had higher average numbers of citations than studies from computer sciences and engineering.
The conducted bibliometric analysis unequivocally reveals the versatile emerging applications of VR and AR in medicine. With the further maturation of the technology and improved accessibility in countries where VR and AR research is strong, we expect it to have a marked impact on clinical practice and in the life of patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
•Top 100 most cited papers in nutraceuticals and functional foods were identified.•The ratio of reviews: original articles was ∼2:1.•USA and Europe were major places of origin.•Focus on prebiotics, ...probiotics, and antioxidants was associated with high citations.•The topic stood in the middle between pharmacognosy/natural products and food science and nutrition.
The current study aimed to identify and analyze the 100 most cited papers on the topic of nutraceuticals and functional foods. Scopus database was searched to extract bibliometric data. Two-thirds of the 100 most cited papers were reviews. Papers were mostly published in food science and nutrition journals, and one-third were published in seven journals, namely: British Journal of Nutrition (6), Critical Reviews in Food Science and Nutrition (6), Journal of Food Science (5), Trends in Food Science and Technology (5), American Journal of Clinical Nutrition (4), Food Chemistry (4) and Journal of Nutrition (4). Topics with high citation counts dealt with prebiotics, probiotics, antioxidants and phenolic content. Hot topics with over 1000 citations per paper include bifidobacterium (1147), colon (1032) and lipid metabolism (1013). The United States and Europe were major places of origin. These results can serve as a quick benchmarking reference for researchers or general public members.
Many researchers have been using the visual analog scale (VAS) to acquire psychometric measurements from participants. Several recent studies have consistently pointed to Hayes and Patterson (1921) ...as the origin of the VAS method. The primary objectives of the current study were to identify the historical root of VAS by cited reference analysis and confirm if it was Hayes and Patterson (1921).
The Web of Science database was searched to identify psychology papers dealing with VAS. The full records and their cited references were extracted and imported into CRExplorer for further analysis. A "reference publication year spectroscopy" (RPYS) was plotted to identify the seminal references.
We analyzed 32,569 references cited by 958 articles. There were 21 RPYS peaks ranging from year 1921 to 2007. We were able to identify (Hayes and Patterson, 1921) from the first peak. Furthermore, we were able to identify a total of seven seminal references that are directly relevant to VAS. Two of them were related to "graphic rating method," three were VAS-validation studies, one was a review on the usage of VAS, and one compared reported results using VAS and Likert scale.
Cited reference analysis with a RPYS plot succeeded in identifying and confirming (Hayes and Patterson, 1921) as the origin of VAS. This method has overcome the limitations of conventional citation analysis, namely the issues of being not indexed, not identified by pre-defined search keywords, and not being all-time most cited.
The increasing use of three-dimensional (3D) imaging techniques in dental medicine has boosted the development and use of artificial intelligence (AI) systems for various clinical problems. Cone beam ...computed tomography (CBCT) and intraoral/facial scans are potential sources of image data to develop 3D image-based AI systems for automated diagnosis, treatment planning, and prediction of treatment outcome. This review focuses on current developments and performance of AI for 3D imaging in dentomaxillofacial radiology (DMFR) as well as intraoral and facial scanning. In DMFR, machine learning-based algorithms proposed in the literature focus on three main applications, including automated diagnosis of dental and maxillofacial diseases, localization of anatomical landmarks for orthodontic and orthognathic treatment planning, and general improvement of image quality. Automatic recognition of teeth and diagnosis of facial deformations using AI systems based on intraoral and facial scanning will very likely be a field of increased interest in the future. The review is aimed at providing dental practitioners and interested colleagues in healthcare with a comprehensive understanding of the current trend of AI developments in the field of 3D imaging in dental medicine.
Food composition databases (FCDBs) are important tools that provide information on the nutritional content of foods. Previously, it was largely unclear what nutritional contents and which FCDBs were ...involved in highly cited papers. The bibliometric study aimed to identify the most productive authors, institutions, and journals. The chemicals/chemical compounds with high averaged citations and FCDBs used by highly cited papers were identified. In July 2023, the online database Web of Science Core Collection (WoSCC) was queried to identify papers related to FCDBs. A total of 803 papers were identified and analyzed. The first paper indexed in WoSCC was published in 1992 by Pennington, which described the usefulness of FCDB for researchers to identify core foods for their own studies. In that paper, the FCDB described was the USDA 1987–88 NFCS (the United States Department of Agriculture 1987–88 Nationwide Food Consumption Survey). The most productive author was Dr. Paul M. Finglas, the Head of the Food Databanks National Capability at the Quadram Institute (Norwich, UK) and the Managing Director of EuroFIR. His most cited paper among this dataset was about the development of an online Irish food composition database together with EuroFIR. The most productive institutions were the USDA and the World Health Organization (WHO) instead of universities. Flavonoid was the most recurring chemical class among the highly cited ones. The anti-oxidative properties and protective effects against heart disease and cancer of flavonoids might be some of the reasons for their popularity in research. Among the highly cited papers, the most heavily used FCDBs were the USDA database for the flavonoid content of selected foods, Fineli, the USDA National Nutrient Database for Standard Reference (USNDB), EuroFIR eBASIS-Bioactive Substances in Food Information Systems, and Phenol-Explorer. High-quality national and international FCDBs should be promoted and made more accessible to the research and public communities to promote better nutrition and public health on a global scale.
Social media has been extensively used for the communication of health-related information and consecutively for the potential spread of medical misinformation. Conventional systematic reviews have ...been published on this topic to identify original articles and to summarize their methodological approaches and themes. A bibliometric study could complement their findings, for instance, by evaluating the geographical distribution of the publications and determining if they were well cited and disseminated in high-impact journals.
The aim of this study was to perform a bibliometric analysis of the current literature to discover the prevalent trends and topics related to medical misinformation on social media.
The Web of Science Core Collection electronic database was accessed to identify relevant papers with the following search string: ALL=(misinformati* OR "wrong informati*" OR disinformati* OR "misleading informati*" OR "fake news*") AND ALL=(medic* OR illness* OR disease* OR health* OR pharma* OR drug* OR therap*) AND ALL=("social media*" OR Facebook* OR Twitter* OR Instagram* OR YouTube* OR Weibo* OR Whatsapp* OR Reddit* OR TikTok* OR WeChat*). Full records were exported to a bibliometric software, VOSviewer, to link bibliographic information with citation data. Term and keyword maps were created to illustrate recurring terms and keywords.
Based on an analysis of 529 papers on medical and health-related misinformation on social media, we found that the most popularly investigated social media platforms were Twitter (n=90), YouTube (n=67), and Facebook (n=57). Articles targeting these 3 platforms had higher citations per paper (>13.7) than articles covering other social media platforms (Instagram, Weibo, WhatsApp, Reddit, and WeChat; citations per paper <8.7). Moreover, social media platform-specific papers accounted for 44.1% (233/529) of all identified publications. Investigations on these platforms had different foci. Twitter-based research explored cyberchondria and hypochondriasis, YouTube-based research explored tobacco smoking, and Facebook-based research studied vaccine hesitancy related to autism. COVID-19 was a common topic investigated across all platforms. Overall, the United States contributed to half of all identified papers, and 80% of the top 10 most productive institutions were based in this country. The identified papers were mostly published in journals of the categories public environmental and occupational health, communication, health care sciences services, medical informatics, and medicine general internal, with the top journal being the Journal of Medical Internet Research.
There is a significant platform-specific topic preference for social media investigations on medical misinformation. With a large population of internet users from China, it may be reasonably expected that Weibo, WeChat, and TikTok (and its Chinese version Douyin) would be more investigated in future studies. Currently, these platforms present research gaps that leave their usage and information dissemination warranting further evaluation. Future studies should also include social platforms targeting non-English users to provide a wider global perspective.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Tooth loss may affect food ingestion and, consequently, nutrition intake. The neuroimaging literature using functional magnetic resonance imaging (fMRI) was reviewed to summarize the changes in brain ...functions in response to denture rehabilitation in patients with partial or complete edentulous dentition. Overall, this review covered nine fMRI studies on denture rehabilitation. Eight recruited complete edentulous patients, whereas one recruited partially edentulous patients. The risk-of-bias assessment revealed concerns regarding all nine studies. Due to the heterogeneity of the studies and the lack of brain coordinates reported, a meta-analysis could not be conducted, and this review could only summarize the findings without statistical validation. The evidence from jaw-clenching studies suggested that implant-supported fixed dentures could be the best option, as compared to implant-supported overdentures and complete dentures, as it was associated with higher brain activity levels in various brain regions, including those corresponding to the primary sensory (postcentral gyrus) and motor cortices (precentral gyrus). Gum-chewing studies indicated that perhaps the medial and middle frontal gyri were associated with food comminuting and food mixing, which could be improved by the full replacement of the dental arch, instead of only partial replacement. All the fMRI studies described the functional neuroplasticity of the patients undergoing denture rehabilitation and suggested that certain rehabilitation options were more beneficial in restoring masticatory functions, as well as their associated brain activity levels.
The primary dimensions of taste are affective value, intensity and quality. Numerous studies have reported the role of the insula in evaluating these dimensions of taste; however, the results were ...inconsistent. Therefore, in the current study, we performed meta-analyses of published data to identify locations consistently activated across studies and evaluate whether different regions of the human brain could be responsible for processing different dimensions of taste. Meta-analyses were performed on 39 experiments, with 846 total healthy subjects (without psychiatric/neurological disorders) in 34 studies reporting whole-brain results. The aim was to establish the activation likelihood estimation (ALE) of taste-mediated regional activation across the whole brain. Apart from one meta-analysis for all studies in general, three analyses were performed to reveal the clusters of activation that were attributable to processing the affective value (data from 323 foci), intensity (data from 43 foci) and quality (data from 45 foci) of taste. The ALE revealed eight clusters of activation outside the insula for processing affective value, covering the middle and posterior cingulate, pre-/post-central gyrus, caudate and thalamus. The affective value had four clusters of activation (two in each hemisphere) in the insula. The intensity and quality activated only the insula, each with one cluster on the right. The concurrence between studies was moderate; at best, 53% of the experiments contributed to the significant clusters attributable to the affective value, 60% to intensity and 50% to quality. The affective value was processed bilaterally in the anterior to middle insula, whereas intensity was processed in the right antero-middle insula, and quality was processed in the right middle insula. The right middle dorsal insula was responsible for processing both the affective value and quality of taste. The exploratory analysis on taste quality did not have a significant result if the studies using liquid food stimuli were excluded. Results from the meta-analyses on studies involving the oral delivery of liquid tastants or liquid food stimuli confirmed that the insula is involved in processing all three dimensions of taste. More experimental studies are required to investigate whether brain activations differ between liquid tastants and food. The coordinates of activated brain areas and brain maps are provided to serve as references for future taste/food studies.
•Data was pooled from 34 whole-brain taste fMRI papers (39 experiments, 846 subjects).•Affective value of taste appeared to be processed by bilateral anterior and middle insula, cingulate cortex, striatum and orbitofrontal cortex•Intensity of taste was processed in right antero-middle insula.•Quality of taste was processed in right middle dorsal insula.•This study provided brain maps and coordinates for future taste/food studies.
Using machine-learning tools to predict individual phenotypes from neuroimaging data is one of the most promising and hence dynamic fields in systems neuroscience. Here, we perform a literature ...survey of the rapidly work on phenotype prediction in healthy subjects or general population to sketch out the current state and ongoing developments in terms of data, analysis methods and reporting. Excluding papers on age-prediction and clinical applications, which form a distinct literature, we identified a total 108 papers published since 2007. In these, memory, fluid intelligence and attention were most common phenotypes to be predicted, which resonates with the observation that roughly a quarter of the papers used data from the Human Connectome Project, even though another half recruited their own cohort. Sample size (in terms of training and external test sets) and prediction accuracy (from internal and external validation respectively) did not show significant temporal trends. Prediction accuracy was negatively correlated with sample size of the training set, but not the external test set. While known to be optimistic, leave-one-out cross-validation (LOO CV) was the prevalent strategy for model validation (n = 48). Meanwhile, 27 studies used external validation with external test set. Both numbers showed no significant temporal trends. The most popular learning algorithm was connectome-based predictive modeling introduced by the Yale team. Other common learning algorithms were linear regression, relevance vector regression (RVR), support vector regression (SVR), least absolute shrinkage and selection operator (LASSO), and elastic net. Meanwhile, the amount of data from self-recruiting studies (but not studies using open, shared dataset) was positively correlated with internal validation prediction accuracy. At the same time, self-recruiting studies also reported a significantly higher internal validation prediction accuracy than those using open, shared datasets. Data type and participant age did not significantly influence prediction accuracy. Confound control also did not influence prediction accuracy after adjusted for other factors. To conclude, most of the current literature is probably quite optimistic with internal validation using LOO CV. More efforts should be made to encourage the use of external validation with external test sets to further improve generalizability of the models.
Multiple reports for brain functional and structural alterations in patients with Crohn’s disease (CD) were published. The current study aimed to meta-analyze the existing neuroimaging data and hence ...produce a brain map revealing areas with functional and structural differences between patients with CD and healthy controls. Original studies published until 2019 were identified from Scopus, Web of Science and PubMed databases, and included into the analysis if they reported relevant results from task-related or resting state functional magnetic resonance imaging (fMRI or rsfMRI) or voxel-based morphometry (VBM), in the form of standardized brain coordinates based on whole-brain analysis. The brain coordinates and sample size of significant results were extracted from eligible studies to be meta-analyzed with the activation likelihood estimation method using the GingerALE software. Sixteen original studies comprised of a total of 865 participants fulfilled the inclusion criteria. Compared to healthy controls, patients with CD had reduced resting state brain connectivity in the paracentral lobule and cingulate gyrus as well as reduced grey matter volume in the medial frontal gyrus. No significant results were found vice versa. These neural correlates allow a better understanding on the effects of CD on the pain expectation, emotion, and quality of life of patients and potentially serve as useful biomarkers for evaluating treatment efficacy.
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