JMIR Med Inform. 2024 Sep 24;12:e58445. doi: 10.2196/58445.

ABSTRACT

BACKGROUND: Data models are crucial for clinical research as they enable researchers to fully use the vast amount of clinical data stored in medical systems. Standardized data and well-defined relationships between data points are necessary to guarantee semantic interoperability. Using the Fast Healthcare Interoperability Resources (FHIR) standard for clinical data representation would be a practical methodology to enhance and accelerate interoperability and data availability for research.

OBJECTIVE: This research aims to provide a comprehensive overview of the state-of-the-art and current landscape in FHIR-based data models and structures. In addition, we intend to identify and discuss the tools, resources, limitations, and other critical aspects mentioned in the selected research papers.

METHODS: To ensure the extraction of reliable results, we followed the instructions of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. We analyzed the indexed articles in PubMed, Scopus, Web of Science, IEEE Xplore, the ACM Digital Library, and Google Scholar. After identifying, extracting, and assessing the quality and relevance of the articles, we synthesized the extracted data to identify common patterns, themes, and variations in the use of FHIR-based data models and structures across different studies.

RESULTS: On the basis of the reviewed articles, we could identify 2 main themes: dynamic (pipeline-based) and static data models. The articles were also categorized into health care use cases, including chronic diseases, COVID-19 and infectious diseases, cancer research, acute or intensive care, random and general medical notes, and other conditions. Furthermore, we summarized the important or common tools and approaches of the selected papers. These items included FHIR-based tools and frameworks, machine learning approaches, and data storage and security. The most common resource was "Observation" followed by "Condition" and "Patient." The limitations and challenges of developing data models were categorized based on the issues of data integration, interoperability, standardization, performance, and scalability or generalizability.

CONCLUSIONS: FHIR serves as a highly promising interoperability standard for developing real-world health care apps. The implementation of FHIR modeling for electronic health record data facilitates the integration, transmission, and analysis of data while also advancing translational research and phenotyping. Generally, FHIR-based exports of local data repositories improve data interoperability for systems and data warehouses across different settings. However, ongoing efforts to address existing limitations and challenges are essential for the successful implementation and integration of FHIR data models.

PMID:39316433 | PMC:PMC11472501 | DOI:10.2196/58445

Perfusion. 2024 Sep 17:2676591241269729. doi: 10.1177/02676591241269729. Online ahead of print.

ABSTRACT

INTRODUCTION: Minimal Invasive Extracorporeal Circulation (MiECC) has recently emerged as a more 'physiologic' alternative to conventional extracorporeal circulation. However, its adoption is still limited due to lack of robust scientific evidence and ongoing debate about its potential benefits. This bibliometric analysis aims to analyze the scientific articles on MiECC and identify current research domains and existing gaps to be addressed in future studies.

METHODS: Pertinent articles were retrieved from the Web of Science (WOS) database. The search string included 'minimal invasive extracorporeal circulation' and its synonyms. The VOSviewer (version 1.6.17) software was used to conduct comprehensive analyses. Semantic and research networks, bibliographic coupling and journal analysis were performed.

RESULTS: Of the 1777 articles identified in WOS, 292 were retrieved. The trend in publications increased from 1991 to date. Most articles focused on transfusion requirements, acute kidney injury, inflammatory markers and cytokines, inflammation and delirium, though the impact of intraoperative optimal fluid and hemodynamic management as far as the occurrence of postoperative complications were poorly addressed. The semantic network analysis found inter-connections between the terms "cardiopulmonary bypass", "inflammatory response", and "cardiac surgery". Perfusion contributed the highest number of published documents. The most extensive research partnerships were between Germany, Greece, Italy, and England.

CONCLUSIONS: Notwithstanding the scientific community's growing interest in MiECC, crucial topics (i.e., the best anesthetic management and intraoperative need for inotropes, vasopressors and fluids) still require more comprehensive exploration. This investigation may prove to be a useful tool for clinicians, scientists, and students concerning global publication output and for the use of MiECC in cardiac surgery.

PMID:39288245 | DOI:10.1177/02676591241269729

JMIR Med Inform. 2024 Sep 17;12:e57853. doi: 10.2196/57853.

ABSTRACT

BACKGROUND: To ensure interoperability, both structural and semantic standards must be followed. For exchanging medical data between information systems, the structural standard FHIR (Fast Healthcare Interoperability Resources) has recently gained popularity. Regarding semantic interoperability, the reference terminology SNOMED Clinical Terms (SNOMED CT), as a semantic standard, allows for postcoordination, offering advantages over many other vocabularies. These postcoordinated expressions (PCEs) make SNOMED CT an expressive and flexible interlingua, allowing for precise coding of medical facts. However, this comes at the cost of increased complexity, as well as challenges in storage and processing. Additionally, the boundary between semantic (terminology) and structural (information model) standards becomes blurred, leading to what is known as the TermInfo problem. Although often viewed critically, the TermInfo overlap can also be explored for its potential benefits, such as enabling flexible transformation of parts of PCEs.

OBJECTIVE: In this paper, an alternative solution for storing PCEs is presented, which involves combining them with the FHIR data model. Ultimately, all components of a PCE should be expressible solely through precoordinated concepts that are linked to the appropriate elements of the information model.

METHODS: The approach involves storing PCEs decomposed into their components in alignment with FHIR resources. By utilizing the Web Ontology Language (OWL) to generate an OWL ClassExpression, and combining it with an external reasoner and semantic similarity measures, a precoordinated SNOMED CT concept that most accurately describes the PCE is identified as a Superconcept. In addition, the nonmatching attribute relationships between the Superconcept and the PCE are identified as the "Delta." Once SNOMED CT attributes are manually mapped to FHIR elements, FHIRPath expressions can be defined for both the Superconcept and the Delta, allowing the identified precoordinated codes to be stored within FHIR resources.

RESULTS: A web application called PCEtoFHIR was developed to implement this approach. In a validation process with 600 randomly selected precoordinated concepts, the formal correctness of the generated OWL ClassExpressions was verified. Additionally, 33 PCEs were used for two separate validation tests. Based on these validations, it was demonstrated that a previously proposed semantic similarity calculation is suitable for determining the Superconcept. Additionally, the 33 PCEs were used to confirm the correct functioning of the entire approach. Furthermore, the FHIR StructureMaps were reviewed and deemed meaningful by FHIR experts.

CONCLUSIONS: PCEtoFHIR offers services to decompose PCEs for storage within FHIR resources. When creating structure mappings for specific subdomains of SNOMED CT concepts (eg, allergies) to desired FHIR profiles, the use of SNOMED CT Expression Templates has proven highly effective. Domain experts can create templates with appropriate mappings, which can then be easily reused in a constrained manner by end users.

PMID:39287966 | PMC:PMC11445620 | DOI:10.2196/57853

Heliyon. 2024 Aug 26;10(17):e36936. doi: 10.1016/j.heliyon.2024.e36936. eCollection 2024 Sep 15.

ABSTRACT

Emergency response plans for tunnel vehicle accidents are crucial to ensure human safety, protect critical infrastructure, and maintain the smooth operation of transportation networks. However, many decision-support systems for emergency responses still rely significantly on predefined response strategies, which may not be sufficiently flexible to manage unexpected or complex incidents. Moreover, existing systems may lack the ability to effectively respond effectively to the impact different emergency scenarios and responses. In this study, semantic web technologies were used to construct a digital decision-support system for emergency responses to tunnel vehicle accidents. A basic digital framework was developed by analysing the knowledge system of the tunnel emergency response, examining its critical elements and intrinsic relationships, and mapping it to the ontology. In addition, the strategies of previous pre-plans are summarised and transformed into semantic rules. Finally, different accident scenarios were modelled to validate the effectiveness of the developed emergency response system.

PMID:39286211 | PMC:PMC11403512 | DOI:10.1016/j.heliyon.2024.e36936

Narra J. 2024 Aug;4(2):e917. doi: 10.52225/narra.v4i2.917. Epub 2024 Aug 5.

ABSTRACT

Since its public release on November 30, 2022, ChatGPT has shown promising potential in diverse healthcare applications despite ethical challenges, privacy issues, and possible biases. The aim of this study was to identify and assess the most influential publications in the field of ChatGPT utility in healthcare using bibliometric analysis. The study employed an advanced search on three databases, Scopus, Web of Science, and Google Scholar, to identify ChatGPT-related records in healthcare education, research, and practice between November 27 and 30, 2023. The ranking was based on the retrieved citation count in each database. The additional alternative metrics that were evaluated included (1) Semantic Scholar highly influential citations, (2) PlumX captures, (3) PlumX mentions, (4) PlumX social media and (5) Altmetric Attention Scores (AASs). A total of 22 unique records published in 17 different scientific journals from 14 different publishers were identified in the three databases. Only two publications were in the top 10 list across the three databases. Variable publication types were identified, with the most common being editorial/commentary publications (n=8/22, 36.4%). Nine of the 22 records had corresponding authors affiliated with institutions in the United States (40.9%). The range of citation count varied per database, with the highest range identified in Google Scholar (1019-121), followed by Scopus (242-88), and Web of Science (171-23). Google Scholar citations were correlated significantly with the following metrics: Semantic Scholar highly influential citations (Spearman's correlation coefficient ρ=0.840, p<0.001), PlumX captures (ρ=0.831, p<0.001), PlumX mentions (ρ=0.609, p=0.004), and AASs (ρ=0.542, p=0.009). In conclusion, despite several acknowledged limitations, this study showed the evolving landscape of ChatGPT utility in healthcare. There is an urgent need for collaborative initiatives by all stakeholders involved to establish guidelines for ethical, transparent, and responsible use of ChatGPT in healthcare. The study revealed the correlation between citations and alternative metrics, highlighting its usefulness as a supplement to gauge the impact of publications, even in a rapidly growing research field.

PMID:39280327 | PMC:PMC11391998 | DOI:10.52225/narra.v4i2.917

J Thorac Cardiovasc Surg. 2024 Sep 14:S0022-5223(24)00809-2. doi: 10.1016/j.jtcvs.2024.09.014. Online ahead of print.

ABSTRACT

BACKGROUND: The task of writing structured content reviews and guidelines has grown stronger and more complex. We propose to go beyond search tools and toward curation tools by automating time-consuming and repetitive steps of extracting and organizing information.

METHODS: SciScribe is built as an extension of IBM's Deep Search platform, which provides document processing and search capabilities. This platform was used to ingest and search full-content publications from PubMed Central (PMC) and official, structured records from the ClinicalTrials and OpenPayments databases. Author names and NCT numbers, mentioned within the publications, were used to link publications to these official records as context. Search strategies involve traditional keyword-based search as well as natural language question and answering via large language models (LLMs).

RESULTS: SciScribe is a web-based tool that helps accelerate literature reviews through key features: (1) accumulating a personal collection from publication sources, such as PMC or other sources; (2) incorporating contextual information from external databases into the presented papers, promoting a more informed assessment by readers; (3) semantic questioning and answering of documents to quickly assess relevance and hierarchical organization; and (4) semantic question answering for each document within a collection, collated into tables.

CONCLUSIONS: Emergent language processing techniques are opening new avenues to accelerate and enhance the literature review process, for which we have demonstrated a use case implementation in cardiac surgery. SciScribe automates and accelerates this process, mitigates errors associated with repetition and fatigue, and contextualizes results by linking relevant external data sources instantaneously.

PMID:39278616 | DOI:10.1016/j.jtcvs.2024.09.014

Sci Data. 2024 Sep 7;11(1):978. doi: 10.1038/s41597-024-03760-9.

ABSTRACT

The United Nations forecast a significant shift in global population distribution by 2050, with rural populations projected to decline. This decline will particularly challenge mountain areas' cultural heritage, well-being, and economic sustainability. Understanding the economic, environmental, and societal effects of rural population decline is particularly important in Europe, where mountainous regions are vital for supplying goods. The present paper describes a geospatially explicit semantic knowledge graph containing information on 454 European mountain value chains. It is the first large-size, structured collection of information on mountain value chains. Our graph, structured through ontology-based semantic modelling, offers representations of the value chains in the form of narratives. The graph was constructed semi-automatically from unstructured data provided by mountain-area expert scholars. It is accessible through a public repository and explorable through interactive Story Maps and a semantic Web service. Through semantic queries, we demonstrate that the graph allows for exploring territorial complexities and discovering new knowledge on mountain areas' environmental, societal, territory, and economic aspects that could help stem depopulation.

PMID:39244629 | PMC:PMC11380662 | DOI:10.1038/s41597-024-03760-9

Health Inf Sci Syst. 2024 Sep 3;12(1):45. doi: 10.1007/s13755-024-00298-3. eCollection 2024 Dec.

ABSTRACT

Adolescent suicide has become an important social issue of general concern. Many young people express their suicidal feelings and intentions through online social media, e.g., Twitter, Microblog. The "tree hole" is the Chinese name for places on the Web where people post secrets. It provides the possibility of using Artificial Intelligence and big data technology to detect the posts where someone express the suicidal signal from those "tree hole" social media. We have developed the Web-based intelligent agents (i.e., AI-based programs) which can monitor the "tree hole" websites in Microblog every day by using knowledge graph technology. We have organized Tree-hole Rescue Team, which consists of more than 1000 volunteers, to carry out suicide rescue intervention according to the daily monitoring notifications. From 2018 to 2023, Tree-hole Rescue Team has prevented more than 6600 suicides. A few thousands of people have been saved within those 6 years. In this paper, we present the basic technology of Web-based Tree Hole intelligent agents and elaborate how the intelligent agents can discover suicide attempts and issue corresponding monitoring notifications and how the volunteers of Tree Hole Rescue Team can conduct online suicide intervention. This research also shows that the knowledge graph approach can be used for the semantic analysis on social media.

PMID:39238574 | PMC:PMC11371955 | DOI:10.1007/s13755-024-00298-3

NPJ Digit Med. 2024 Sep 3;7(1):231. doi: 10.1038/s41746-024-01225-2.

ABSTRACT

Deep learning for computer vision can be leveraged for interpreting surgical scenes and providing surgeons with real-time guidance to avoid complications. However, neither generalizability nor scalability of computer-vision-based surgical guidance systems have been demonstrated, especially to geographic locations that lack hardware and infrastructure necessary for real-time inference. We propose a new equipment-agnostic framework for real-time use in operating suites. Using laparoscopic cholecystectomy and semantic segmentation models for predicting safe/dangerous ("Go"/"No-Go") zones of dissection as an example use case, this study aimed to develop and test the performance of a novel data pipeline linked to a web-platform that enables real-time deployment from any edge device. To test this infrastructure and demonstrate its scalability and generalizability, lightweight U-Net and SegFormer models were trained on annotated frames from a large and diverse multicenter dataset from 136 institutions, and then tested on a separate prospectively collected dataset. A web-platform was created to enable real-time inference on any surgical video stream, and performance was tested on and optimized for a range of network speeds. The U-Net and SegFormer models respectively achieved mean Dice scores of 57% and 60%, precision 45% and 53%, and recall 82% and 75% for predicting the Go zone, and mean Dice scores of 76% and 76%, precision 68% and 68%, and recall 92% and 92% for predicting the No-Go zone. After optimization of the client-server interaction over the network, we deliver a prediction stream of at least 60 fps and with a maximum round-trip delay of 70 ms for speeds above 8 Mbps. Clinical deployment of machine learning models for surgical guidance is feasible and cost-effective using a generalizable, scalable and equipment-agnostic framework that lacks dependency on hardware with high computing performance or ultra-fast internet connection speed.

PMID:39227660 | DOI:10.1038/s41746-024-01225-2

Biomolecules. 2024 Aug 20;14(8):1033. doi: 10.3390/biom14081033.

ABSTRACT

The development of new treatments for neglected tropical diseases (NTDs) remains a major challenge in the 21st century. In most cases, the available drugs are obsolete and have limitations in terms of efficacy and safety. The situation becomes even more complex when considering the low number of new chemical entities (NCEs) currently in use in advanced clinical trials for most of these diseases. Natural products (NPs) are valuable sources of hits and lead compounds with privileged scaffolds for the discovery of new bioactive molecules. Considering the relevance of biodiversity for drug discovery, a chemoinformatics analysis was conducted on a compound dataset of NPs with anti-trypanosomatid activity reported in 497 research articles from 2019 to 2024. Structures corresponding to different metabolic classes were identified, including terpenoids, benzoic acids, benzenoids, steroids, alkaloids, phenylpropanoids, peptides, flavonoids, polyketides, lignans, cytochalasins, and naphthoquinones. This unique collection of NPs occupies regions of the chemical space with drug-like properties that are relevant to anti-trypanosomatid drug discovery. The gathered information greatly enhanced our understanding of biologically relevant chemical classes, structural features, and physicochemical properties. These results can be useful in guiding future medicinal chemistry efforts for the development of NP-inspired NCEs to treat NTDs caused by trypanosomatid parasites.

PMID:39199420 | DOI:10.3390/biom14081033

Stud Health Technol Inform. 2024 Aug 22;316:1406-1410. doi: 10.3233/SHTI240674.

ABSTRACT

Real-world data (RWD) (i.e., data from Electronic Healthcare Records - EHRs, ePrescription systems, patient registries, etc.) gain increasing attention as they could support observational studies on a large scale. OHDSI is one of the most prominent initiatives regarding the harmonization of RWD and the development of relevant tools via the use of a common data model, OMOP-CDM. OMOP-CDM is a crucial step towards syntactic and semantic data interoperability. Still, OMOP-CDM is based on a typical relational database format, and thus, the vision of a fully connected semantically enriched model is not fully realized. This work presents an open-source effort to map the OMOP-CDM model and the data it hosts, to an ontological model using RDF to support the FAIRness of RWD and their interlinking with Linked Open Data (LOD) towards the vision of the Semantic Web.

PMID:39176643 | DOI:10.3233/SHTI240674

Stud Health Technol Inform. 2024 Aug 22;316:1785-1789. doi: 10.3233/SHTI240777.

ABSTRACT

Rare diseases pose significant challenges due to their heterogeneity and lack of knowledge. This study develops a comprehensive pipeline interoperable with a document-oriented clinical data warehouse, integrating cohort characterization, patient clustering and interpretation. Leveraging NLP, semantic similarity, machine learning and visualization, the pipeline enables the identification of prevalent phenotype patterns and patient stratification. To enhance interpretability, discriminant phenotypes characterizing each cluster are provided. Users can visually test hypotheses by marking patients exhibiting specific keywords in the EHR like genes, drugs and procedures. Implemented through a web interface, the pipeline enables clinicians to navigate through different modules, discover intricate patterns and generate interpretable insights that may advance rare diseases understanding, guide decision-making, and ultimately improve patient outcomes.

PMID:39176563 | DOI:10.3233/SHTI240777

Stud Health Technol Inform. 2024 Aug 22;316:1463-1464. doi: 10.3233/SHTI240689.

ABSTRACT

This paper presents a versatile solution to formally represent the contents of electronic health records. It is based on the knowledge graph paradigm, and semantic web standards RDF and OWL. It employs the established semantic standards SNOMED CT and FHIR, which warrant international interoperability. A graph-based form is not only useful to feed different target visualizations, but it can also be subject to AI-powered services such as (fuzzy) retrieval and summarization.

PMID:39176479 | DOI:10.3233/SHTI240689

Nat Hum Behav. 2024 Aug 22. doi: 10.1038/s41562-024-01957-x. Online ahead of print.

ABSTRACT

How does scientific knowledge grow? This question has occupied a central place in the philosophy of science, stimulating heated debates but yielding no clear consensus. Many explanations can be understood in terms of whether and how they view the expansion of knowledge as proceeding through the accretion of scientific concepts into larger conceptual structures. Here we examine these views empirically by analysing 2,605,224 papers spanning five decades from both the social sciences (Web of Science) and the physical sciences (American Physical Society). Using natural language processing techniques, we create semantic networks of concepts, wherein noun phrases become linked when used in the same paper abstract. We then detect the core/periphery structures of these networks, wherein core concepts are densely connected sets of highly central nodes and periphery concepts are sparsely connected nodes that are highly connected to the core. For both the social and physical sciences, we observe increasingly rigid conceptual cores accompanied by the proliferation of periphery concepts. Subsequently, we examine the relationship between conceptual structure and the growth of scientific knowledge, finding that scientific works are more innovative in fields with cores that have higher conceptual churn and with larger cores. Furthermore, scientific consensus is associated with reduced conceptual churn and fewer conceptual cores. Overall, our findings suggest that while the organization of scientific concepts is important for the growth of knowledge, the mechanisms vary across time.

PMID:39174726 | DOI:10.1038/s41562-024-01957-x

BMC Infect Dis. 2024 Aug 15;24(1):828. doi: 10.1186/s12879-024-09736-9.

ABSTRACT

BACKGROUND: Malaria is a serious, fatal disease, and a high-risk determinant for human health globally. Children, pregnant women, and migrants are vulnerable groups for malaria infection in African regions. Recently, malaria is an endemic disease in Ethiopia.

OBJECTIVES: This study aimed to determine the pooled prevalence of malaria and its determinant factors among the most vulnerable populations in Ethiopia.

METHODS: Electronic databases, including PubMed, Google Scholar, Web of Science, Semantic Scholar, and Scopus were used for searching articles published since the 2020 Gregorian calendar and onwards. All peer-reviewed Ethiopian journals, health institutions, and Universities were considered for article searching. A PRISMA flow chart and Endnote software were used for article screening, and to remove duplications, respectively. The modified version of the Newcastle-Ottawa Scale was used for potential risk of bias assessments. The heterogeneity among the included studies was evaluated using the indicator of heterogeneity (I2). Egger's test and funnel plot were used to examine the possible publication bias. A random-effects analysis was used to assess the pooled prevalence of malaria, and its determinant factors with a 95% CI. The screening process, data extraction, and quality assessment were done independently, and any disagreements were resolved through discussions.

RESULTS: A total of twelve studies were included in this study. The pooled malaria prevalence was 11.10% (95% CI: 6.10, 16.11). Stagnant water (AOR: 4.19, 95% CI: 2.47, 7.11), no insecticide-treated net utilization (AOR: 3.15, 95% CI: 1.73, 5.73), and staying outdoors at night (AOR: 5.19, 95% CI: 2.08, 12.94) were the pooled estimated statistically risk factors for malaria prevalence. Whereas, insecticide-treated bed net utilization (AOR: 1.59, 95% CI: 0.23, 10.95) reduces the risk of malaria infection.

CONCLUSIONS: The pooled prevalence of malaria is high among vulnerable populations. Creating awareness regarding utilization of insecticide-treated bed nets, and draining stagnant water from the environment are possible interventions to reduce the prevalence of malaria.

PMID:39148027 | DOI:10.1186/s12879-024-09736-9

JMIR Hum Factors. 2024 Aug 15;11:e57670. doi: 10.2196/57670.

ABSTRACT

BACKGROUND: The rapid growth of web-based medical services has highlighted the significance of smart triage systems in helping patients find the most appropriate physicians. However, traditional triage methods often rely on department recommendations and are insufficient to accurately match patients' textual questions with physicians' specialties. Therefore, there is an urgent need to develop algorithms for recommending physicians.

OBJECTIVE: This study aims to develop and validate a patient-physician hybrid recommendation (PPHR) model with response metrics for better triage performance.

METHODS: A total of 646,383 web-based medical consultation records from the Internet Hospital of the First Affiliated Hospital of Xiamen University were collected. Semantic features representing patients and physicians were developed to identify the set of most similar questions and semantically expand the pool of recommended physician candidates, respectively. The physicians' response rate feature was designed to improve candidate rankings. These 3 characteristics combine to create the PPHR model. Overall, 5 physicians participated in the evaluation of the efficiency of the PPHR model through multiple metrics and questionnaires as well as the performance of Sentence Bidirectional Encoder Representations from Transformers and Doc2Vec in text embedding.

RESULTS: The PPHR model reaches the best recommendation performance when the number of recommended physicians is 14. At this point, the model has an F1-score of 76.25%, a proportion of high-quality services of 41.05%, and a rating of 3.90. After removing physicians' characteristics and response rates from the PPHR model, the F1-score decreased by 12.05%, the proportion of high-quality services fell by 10.87%, the average hit ratio dropped by 1.06%, and the rating declined by 11.43%. According to whether those 5 physicians were recommended by the PPHR model, Sentence Bidirectional Encoder Representations from Transformers achieved an average hit ratio of 88.6%, while Doc2Vec achieved an average hit ratio of 53.4%.

CONCLUSIONS: The PPHR model uses semantic features and response metrics to enable patients to accurately find the physician who best suits their needs.

PMID:39146009 | DOI:10.2196/57670

Disabil Rehabil Assist Technol. 2024 Aug 14:1-10. doi: 10.1080/17483107.2024.2387101. Online ahead of print.

ABSTRACT

INTRODUCTION: A modern and accessible healthcare system requires digital innovation and connectivity. The term "Digital health" covers vide range technologies, such as mobile health and applications, electronic records, telehealth and telemedicine, wearable devices, robotics, virtual reality and artificial intelligence.

METHODS: Scientometrics is the method that we have done in this study by Cite Space and VOSviewer software, and the result of searching the Web of Science database in plain text format to perform analysis and scientometrics and create outputs in the form of graphs and tables in the field of digital health has been used in stroke rehabilitation.

RESULT: A total of 2933 documents related to digital health technologies in stroke rehabilitation were identified by searching for the terms "stroke rehabilitation" or "stroke recovery" in the title and "digital health" across all fields. The strongest citations related to cerebrovascular disease spanned from 1994 to 2007, with randomised clinical trials occurring almost simultaneously and ended by 2012. Consequently, stroke rehabilitation by virtual reality technology has obtained the most citations and clinical trials and as an important part of digital health in the future research process.

CONCLUSION: This scientometric study offers insights into how digital health technology can assist stroke patients in self-managing their health and well-being, in addition to supporting integrated stroke rehabilitation. The analysis revealed that three themes were present: author contributors and collaboration networks, temporal evolution, the strongest citation explosions for digital health technologies in stroke rehabilitation research, and semantic analysis.

PMID:39140131 | DOI:10.1080/17483107.2024.2387101

Psychol Res. 2024 Aug 6. doi: 10.1007/s00426-024-02018-8. Online ahead of print.

ABSTRACT

In real-world scenes, the different objects and events are often interconnected within a rich web of semantic relationships. These semantic links help parse information efficiently and make sense of the sensory environment. It has been shown that, during goal-directed search, hearing the characteristic sound of an everyday life object helps finding the affiliate objects in artificial visual search arrays as well as in naturalistic, real-life videoclips. However, whether crossmodal semantic congruence also triggers orienting during spontaneous, not goal-directed observation is unknown. Here, we investigated this question addressing whether crossmodal semantic congruence can attract spontaneous, overt visual attention when viewing naturalistic, dynamic scenes. We used eye-tracking whilst participants (N = 45) watched video clips presented alongside sounds of varying semantic relatedness with objects present within the scene. We found that characteristic sounds increased the probability of looking at, the number of fixations to, and the total dwell time on semantically corresponding visual objects, in comparison to when the same scenes were presented with semantically neutral sounds or just with background noise only. Interestingly, hearing object sounds not met with an object in the scene led to increased visual exploration. These results suggest that crossmodal semantic information has an impact on spontaneous gaze on realistic scenes, and therefore on how information is sampled. Our findings extend beyond known effects of object-based crossmodal interactions with simple stimuli arrays and shed new light on the role that audio-visual semantic relationships out in the perception of everyday life scenarios.

PMID:39105825 | DOI:10.1007/s00426-024-02018-8

J Palliat Med. 2024 Aug 2. doi: 10.1089/jpm.2024.0007. Online ahead of print.

ABSTRACT

Background and Objectives: Spiritual care is an essential component of care for the terminally ill, because of its potential to positively impact patient perception of quality of life and dignity. However, it continues to be the least cultivated or even most overlooked aspect of palliative care and end of life. We performed a methodological review using bibliometric analysis to provide a holistic view of the scientific output published on this topic in the literature at the same time outlining present perspectives and research trends. Methods: In accordance with the BIBLIO checklist for reporting the bibliometric reviews of the biomedical literature, pertinent articles were retrieved from the Web of Science (WOS) database. The search string included "spiritual care," "end of life," and their synonyms. The VOSviewer (version 1.6.17) software was used to conduct comprehensive analyses. Semantic and research networks, bibliographic coupling, and journal analysis were examined. Results: A total of 924 articles were identified in WOS, and 842 were retrieved. An increasing trend in the number of publications is observed from 1981 to date, with a peak in the 2019-2021 timeframe. Most articles focused on palliative care, spirituality, spiritual care, religion, end of life, and cancer. The Journal of Pain and Symptom Management contributed the highest number of published documents, while the Journal of Palliative Medicine was the top-cited journal. The highest number of publications originated from collaborations of authors from the United Kingdom, the United States, and Australia. Conclusion: The remarkable increase in the number of publications on spiritual care observed in the years of the COVID-19 pandemic likely reflected global concerns, reasserting the importance of prioritizing spiritual care for whole-person palliation. Spiritual care is integrated with palliative care, in line with the latter's holistic nature and the recognition of spirituality as a fundamental aspect of end-of-life care. Nurses and chaplains exhibited more involvement in palliative-spiritual care than physicians reflecting the belief that chaplains are perceived as specialized providers, and nurses, owing to their direct exposure to spiritual suffering and ethos, are deemed suitable for providing spiritual care.

PMID:39093919 | DOI:10.1089/jpm.2024.0007

Clin J Gastroenterol. 2024 Jul 30. doi: 10.1007/s12328-024-02010-0. Online ahead of print.

ABSTRACT

We present a unique case of a prepyloric gastric muscular ring, a pathology distinct from a gastric web. There is scarcity of literature on this topic, nearly all cases of prepyloric antral rings or webs published in literature are mucosal or submucosal in nature with no evidence of muscle hypertrophy. Given the prevalence of pyloric stenosis as the most common gastric outlet malformation in neonates, gastric rings and webs are not readily considered in the differential diagnosis of gastric outlet obstruction. While most cases of gastric outlet obstruction are diagnosed radiologically, less common pathologies will be confirmed with direct visual inspection during surgery. The term "congenital gastric outlet obstruction" has been used to encompass rare cases, making it appropriate to include a muscular ring in this category. We propose the term "gastric ring" be used with a semantic modifier of "muscular" versus "submucosal/mucosal" to avoid confusion.

PMID:39080179 | DOI:10.1007/s12328-024-02010-0