Epidemiol Infect. 2023 Feb 27;151:e46. doi: 10.1017/S0950268823000316.

ABSTRACT

Surveillance is a key public health function to enable early detection of infectious disease events and inform public health action. Data linkage may improve the depth of data for response to infectious disease events. This study aimed to describe the uses of linked data for infectious disease events. A systematic review was conducted using Pubmed, CINAHL and Web of Science. Studies were included if they used data linkage for an acute infectious disease event (e.g. outbreak of disease). We summarised the event, study aims and designs; data sets; linkage methods; outcomes reported; and benefits and limitations. Fifty-four studies were included. Uses of linkage for infectious disease events included assessment of severity of disease and risk factors; improved case finding and contact tracing; and vaccine uptake, safety and effectiveness. The ability to conduct larger scale population level studies was identified as a benefit, in particular for rarer exposures, risk factors or outcomes. Limitations included timeliness, data quality and inability to collect additional variables. This review demonstrated multiple uses of data linkage for infectious disease events. As infectious disease events occur without warning, there is a need to establish pre-approved protocols and the infrastructure for data-linkage to enhance information available during an event.

PMID:36843485 | DOI:10.1017/S0950268823000316

Int J Environ Res Public Health. 2023 Feb 13;20(4):3293. doi: 10.3390/ijerph20043293.

ABSTRACT

This study compared the reliability, construct validity, and respondents' preference of the Chinese version of 8-item eHEALS (C-eHEALS) and 21-item DHLI (C-DHLI) in assessing older adults' electronic health (eHealth) literacy using a mixed-methods approach. A web-based, cross-sectional survey was conducted among 277 Chinese older adults from September to October 2021, and 15 respondents were subsequently interviewed to understand their preference of scale to use in practice. Results showed that the internal consistency and test-retest reliability of both scales were satisfactory. For the construct validity, the C-DHLI score showed stronger positive correlations with having Internet use for health information and higher educational attainments, occupational skill levels, self-rated Internet skills, and health literacy than the C-eHEALS score. In addition, younger age, higher household income, urban residence, and longer Internet use history were only positively correlated with C-DHLI score. Qualitative data suggested that most interviewees perceived the C-DHLI as more readable than C-eHEALS for its clear structure, specific description, short sentence length, and less semantic complexity. Findings revealed that both scales are reliable tools to measure eHealth literacy among Chinese older adults, and the C-DHLI seemed to be a more valid and favored instrument for the general Chinese older population based on the quantitative and qualitative results.

PMID:36833987 | DOI:10.3390/ijerph20043293

PLoS One. 2023 Feb 24;18(2):e0281348. doi: 10.1371/journal.pone.0281348. eCollection 2023.

ABSTRACT

This article describes the adaptation of a non-spatial model of pastureland dynamics, including vegetation life cycle, livestock management and nitrogen cycle, for use in a spatially explicit and modular modelling platform (k.LAB) dedicated to make data and models more interoperable. The aim is to showcase to the social-ecological modelling community the delivery of an existing, monolithic model, into a more modular, transparent and accessible approach to potential end users, regional managers, farmers and other stakeholders. This also allows better usability and adaptability of the model beyond its originally intended geographical scope (the Cantabrian Region in the North of Spain). The original code base (written in R in 1,491 lines of code divided into 13 files) combines several algorithms drawn from the literature in an opaque fashion due to lack of modularity, non-semantic variable naming and implicit assumptions. The spatiotemporal rewrite is structured around a set of 10 namespaces called PaL (Pasture and Livestock), which includes 198 interoperable and independent models. The end user chooses the spatial and temporal context of the analysis through an intuitive web-based user interface called k.Explorer. Each model can be called individually or in conjunction with the others, by querying any PaL-related concepts in a search bar. A scientific dataflow and a provenance diagram are produced in conjunction with the model results for full transparency. We argue that this work demonstrates key steps needed to create more Findable, Accessible, Interoperable and Reusable (FAIR) models beyond the selected example. This is particularly essential in environments as complex as agricultural systems, where multidisciplinary knowledge needs to be integrated across diverse spatial and temporal scales in order to understand complex and changing problems.

PMID:36827966 | DOI:10.1371/journal.pone.0281348

PLOS Digit Health. 2022 Oct 10;1(10):e0000118. doi: 10.1371/journal.pdig.0000118. eCollection 2022 Oct.

ABSTRACT

Lack of interoperability and integration between heterogeneous health systems is a big challenge to realize the potential benefits of eHealth. To best move from siloed applications to interoperable eHealth solutions, health information exchange (HIE) policy and standards are necessary to be established. However, there is no comprehensive evidence on the current status of HIE policy and standards on the African continent. Therefore, this paper aimed to systematically review the status of HIE policy and standards which are currently in practice in Africa. A systematic search of the literature was conducted from Medical Literature Analysis and Retrieval System Online (MEDLINE), Scopus, Web of Science, and Excerpta Medica Database (EMBASE), and a total of 32 papers (21 strategic documents and 11 peer-reviewed papers) were selected based on predefined criteria for synthesis. Results revealed that African countries have paid attention to the development, improvement, adoption, and implementation of HIE architecture for interoperability and standards. Synthetic and semantic interoperability standards were identified for the implementation of HIE in Africa. Based on this comprehensive review, we recommend that comprehensive interoperable technical standards should be set at each national level and should be guided by appropriate governance and legal frameworks, data ownership and use agreements, and health data privacy and security guidelines. On top of the policy issues, there is a need to identify a set of standards (health system standards, communication, messaging standards, terminology/vocabulary standards, patient profile standards, privacy and security, and risk assessment) and implement them throughout all levels of the health system. On top of this, we recommend that the Africa Union (AU) and regional bodies provide the necessary human resource and high-level technical support to African countries to implement HIE policy and standards. To realize the full potential of eHealth in the continent, it is recommended that African countries need to have a common HIE policy, interoperable technical standards, and health data privacy and security guidelines. Currently, there is an ongoing effort by the Africa Centres for Disease Control and Prevention (Africa CDC) towards promoting HIE on the continent. A task force has been established from Africa CDC, Health Information Service Provider (HISP) partners, and African and global HIE subject matter experts to provide expertise and guidance in the development of AU policy and standards for HIE. Although the work is still ongoing, the African Union shall continue to support the implementation of HIE policy and standards in the continent. The authors of this review are currently working under the umbrella of the African Union to develop the HIE policy and standard to be endorsed by the head of states of the Africa Union. As a follow-up publication to this, the result will be published in mid-2022.

PMID:36812615 | DOI:10.1371/journal.pdig.0000118

Healthcare (Basel). 2023 Jan 30;11(3):390. doi: 10.3390/healthcare11030390.

ABSTRACT

Although Health Level Seven (HL 7) message standards (v2, v3, Clinical Document Architecture (CDA)) have been commonly adopted, there are still issues associated with them, especially the semantic interoperability issues and lack of support for smart devices (e.g., smartphones, fitness trackers, and smartwatches), etc. In addition, healthcare organizations in many countries are still using proprietary electronic health record (EHR) message formats, making it challenging to convert to other data formats-particularly the latest HL7 Fast Health Interoperability Resources (FHIR) data standard. The FHIR is based on modern web technologies such as HTTP, XML, and JSON and would be capable of overcoming the shortcomings of the previous standards and supporting modern smart devices. Therefore, the FHIR standard could help the healthcare industry to avail the latest technologies benefits and improve data interoperability. The data representation and mapping from the legacy data standards (i.e., HL7 v2 and EHR) to the FHIR is necessary for the healthcare sector. However, direct data mapping or conversion from the traditional data standards to the FHIR data standard is challenging because of the nature and formats of the data. Therefore, in this article, we propose a framework that aims to convert proprietary EHR messages into the HL7 v2 format and apply an unsupervised clustering approach using the DBSCAN (density-based spatial clustering of applications with noise) algorithm to automatically group a variety of these HL7 v2 messages regardless of their semantic origins. The proposed framework's implementation lays the groundwork to provide a generic mapping model with multi-point and multi-format data conversion input into the FHIR. Our experimental results show the proposed framework's ability to automatically cluster various HL7 v2 message formats and provide analytic insight behind them.

PMID:36766965 | DOI:10.3390/healthcare11030390

Radiographics. 2023 Mar;43(3):e220098. doi: 10.1148/rg.220098.

ABSTRACT

From basic research to the bedside, precise terminology is key to advancing medicine and ensuring optimal and appropriate patient care. However, the wide spectrum of diseases and their manifestations superimposed on medical team-specific and discipline-specific communication patterns often impairs shared understanding and the shared use of common medical terminology. Common terms are currently used in medicine to ensure interoperability and facilitate integration of biomedical information for clinical practice and emerging scientific and educational applications alike, from database integration to supporting basic clinical operations such as billing. Such common terminologies can be provided in ontologies, which are formalized representations of knowledge in a particular domain. Ontologies unambiguously specify common concepts and describe the relationships between those concepts by using a form that is mathematically precise and accessible to humans and machines alike. RadLex® is a key RSNA initiative that provides a shared domain model, or ontology, of radiology to facilitate integration of information in radiology education, clinical care, and research. As the contributions of the computational components of common radiologic workflows continue to increase with the ongoing development of big data, artificial intelligence, and novel image analysis and visualization tools, the use of common terminologies is becoming increasingly important for supporting seamless computational resource integration across medicine. This article introduces ontologies, outlines the fundamental semantic web technologies used to create and apply RadLex, and presents examples of RadLex applications in everyday radiology and research. It concludes with a discussion of emerging applications of RadLex, including artificial intelligence applications. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.

PMID:36757882 | DOI:10.1148/rg.220098

J Paediatr Child Health. 2023 Apr;59(4):644-652. doi: 10.1111/jpc.16364. Epub 2023 Feb 6.

ABSTRACT

AIM: To describe the cumulative incidence of child protection (CP) system contact, maltreatment type, source of reports to age 7 years, and socio-demographic characteristics for culturally and linguistically diverse (CALD) Australian children.

METHODS: We used CP, education, health, and birth registrations data for children followed from birth up to age 7 from the South Australian Better Evidence, Better Outcomes, Linked Data (SA BEBOLD) platform.

PARTICIPANTS: SA born children enrolled in their first year of school from 2009 to 2015 (n = 76 563). CALD defined as non-Aboriginal or Torres Strait Islander, spoken language other than English, Indigenous or Sign, or had at least one parent born in a non-English speaking country.

OUTCOMES MEASURES: For CALD and non-CALD children, we estimated the cumulative incidence (risk) of CP contacts up to age 7, relative risk and risk differences for all levels of CP contact from notification to out-of-home care (OOHC), primary maltreatment type, reporter type, and socio-economic characteristics. Sensitivity analyses explored different population selection criteria and CALD definitions.

RESULTS: By age 7, 11.2% of CALD children had 'screened-in' notifications compared to 18.8% of non-CALD (risk difference [RD] 7.6 percentage points (95% confidence interval: 6.9-8.3)), and 0.6% of CALD children experienced OOHC compared to 2.2% of non-CALD (RD 1.6 percentage points (95% confidence interval: 1.3-1.8)). Emotional abuse was the most common substantiated maltreatment type for CALD and neglect for non-CALD. Among both groups, the most common reporter sources were police and education sector. Socio-economic characteristics were broadly similar. Sensitivity analyses results were consistent with primary analyses.

CONCLUSION: By age 7, CALD children had lower risk of contact with all levels of CP. Estimates based on primary and sensitivity analyses suggested CALD children were 5-9 percentage points less likely to have a report screened-in, and from 1.0 to 1.7 percentage points less likely to have experienced OOHC.

PMID:36744551 | DOI:10.1111/jpc.16364

Front Neurorobot. 2023 Jan 18;16:988024. doi: 10.3389/fnbot.2022.988024. eCollection 2022.

ABSTRACT

With the rapid development of web technologies and the popularity of smartphones, users are uploading and sharing a large number of images every day. Therefore, it is a very important issue nowadays to enable users to discover exactly the information they need in the vast amount of data and to make it possible to integrate their large amount of image material efficiently. However, traditional content-based image retrieval techniques are based on images, and there is a "semantic gap" between this and people's understanding of images. To address this "semantic gap," a keyframe image processing method for 3D point clouds is proposed, and based on this, a U-Net-based binary data stream semantic segmentation network is established for keyframe image processing of 3D point clouds in combination with deep learning techniques.

PMID:36742192 | PMC:PMC9890954 | DOI:10.3389/fnbot.2022.988024

J Integr Neurosci. 2023 Jan 17;22(1):24. doi: 10.31083/j.jin2201024.

ABSTRACT

BACKGROUND: The left primary motor area (M1) stimulation has recently been revealed to promote post-stroke aphasia (PSA) recovery, of which a plausible mechanism might be the semantic and/or the mirror neuron system reorganization, but the direct evidence is still scarce. The aim of this study was to explore the functional connectivity (FC) alterations induced by the left M1 intermittent theta burst stimulation (iTBS), a new transcranial magnetic stimulation paradigm, in the semantic and mirror neuron systems of PSA patients.

METHODS: Sixteen PSA patients accepted the left M1 iTBS and underwent a resting-state functional magnetic resonance image (fMRI) scanning before and immediately after the first session of iTBS, of which six underwent another fMRI scanning after twenty sessions of iTBS. Three brain networks covering the semantic and the mirror neuron systems were constructed using the fMRI data, and the FC alterations following one-session iTBS were investigated in the networks. Additional seed-based FC analyses were conducted to explore the longitudinal FC patterns changes during the course of multi-session iTBS. The Aphasia quotient of the Chinese version of the western aphasia battery (WAB-AQ) was used to assess the severity of the language impairments of the participants. The relationship between the longitudinal WAB-AQ and network FC changes was analyzed by Spearman's correlation coefficients in the multi-session iTBS sub-group.

RESULTS: Decreased FCs were noted in the bilateral semantic rather than in the mirror neuron networks following one-session of iTBS (p < 0.05, network based statistical corrected). Longitudinal seed-based FC analyses revealed changing FC ranges along the multi-session iTBS course, extending beyond the semantic networks. No significant relationship was found between the longitudinal WAB-AQ and network FC changes in the multi-session iTBS sub-group.

CONCLUSIONS: The left M1 iTBS might induce FC changes in the semantic system of PSA patients.

CLINICAL TRIAL REGISTRATION: This research was registered on the Chinese Clinical Trial Registry website (http://www.chictr.org.cn/index.aspx), and the registration number is ChiCTR2100041936.

PMID:36722227 | DOI:10.31083/j.jin2201024

BMC Geriatr. 2023 Jan 31;23(1):58. doi: 10.1186/s12877-023-03770-z.

ABSTRACT

BACKGROUND: While several definitions exist for multimorbidity, frailty or polypharmacy, it is yet unclear to what extent single healthcare markers capture the complexity of health-related needs in older people in the community. We aimed to identify and characterise older people with complex health needs based on healthcare resource use (unplanned hospitalisations or polypharmacy) or frailty using large population-based linked records.

METHODS: In this cohort study, data was extracted from UK primary care records (CPRD GOLD), with linked Hospital Episode Statistics inpatient data. People aged > 65 on 1st January 2010, registered in CPRD for ≥ 1 year were included. We identified complex health needs as the top quintile of unplanned hospitalisations, number of prescribed medicines, and electronic frailty index. We characterised all three cohorts, and quantified point-prevalence and incidence rates of preventive medicines use.

RESULTS: Overall, 90,597, 110,225 and 116,076 individuals were included in the hospitalisation, frailty, and polypharmacy cohorts respectively; 28,259 (5.9%) were in all three cohorts, while 277,332 (58.3%) were not in any (background population). Frailty and polypharmacy cohorts had the highest bi-directional overlap. Most comorbidities such as diabetes and chronic kidney disease were more common in the frailty and polypharmacy cohorts compared to the hospitalisation cohort. Generally, prevalence of preventive medicines use was highest in the polypharmacy cohort compared to the other two cohorts: For instance, one-year point-prevalence of statins was 64.2% in the polypharmacy cohort vs. 60.5% in the frailty cohort.

CONCLUSIONS: Three distinct groups of older people with complex health needs were identified. Compared to the hospitalisation cohort, frailty and polypharmacy cohorts had more comorbidities and higher preventive therapies use. Research is needed into the benefit-risk of different definitions of complex health needs and use of preventive therapies in the older population.

PMID:36721104 | DOI:10.1186/s12877-023-03770-z

J Stomatol Oral Maxillofac Surg. 2023 Jan 28:101404. doi: 10.1016/j.jormas.2023.101404. Online ahead of print.

ABSTRACT

Alloplastic total temporomandibular joint replacement (TMJR) is the treatment of choice for end-stage temporomandibular joint diseases. Extended TMJR (eTMJR) is a modification of the standard alloplastic fossa-condyle joint that includes components extending further to the skull base or the mandible. The aim of this study is to review the use of the eTMJR prosthesis for the treatment of large craniomaxillofacial defects. Online data mining was performed according to the PRISMA statement using online search in databases such as PubMed (Medline), Google Scholar, Dimensions, Semantic Scholar and Web of Science. A total of 19 case reports, 08 case series and 03 retrospective studies were identified. A total of 49 patients were presented in the case reports and case series, who were implanted with 56 eTMJR prostheses (07 bilateral and 42 unilateral procedures). The mean age of the patients was 36.02±16.54 years, the male to female patient ratio was 1:1.72 and the mean follow-up time was 23.74 ± 19.83 months. The eTMJR prosthesis was most frequently used to treat ameloblastoma and hemifacial microsomia. Analysis of the retrospective studies was performed in three domains: the baseline characteristic of patients, treatment outcomes in terms of functional variables and complications after eTMJR prostheses implantation. This study concluded that the implantion of the eTMJR prosthesis was uncommon, that appropriate class of eTMJR prosthesis was not reported, and that the width of the mandibular component (like the length) of eTMJR prosthesis has substantial variations.

PMID:36720364 | DOI:10.1016/j.jormas.2023.101404

Clin Psychol Psychother. 2023 Jan 30. doi: 10.1002/cpp.2836. Online ahead of print.

ABSTRACT

OBJECTIVES: The purpose of this systematic review (SR) was to present the current state of research on historical trauma, and the topics closely related to its semantic space that include intergenerational trauma, collective trauma, and extended cultural bodily and mental responses, in order to identify gaps in the literature that need to be addressed.

METHODS: A search of empirical studies from 1990-2022 was performed via Scopus, Web of Science, MEDLINE, EBSCOhost-PsychInfo, and Embase, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist RESULTS: The initial search yielded 1012 studies, 52 of which were included in the current review. The results show that the historical trauma concept has a high potential for new research in the field of Global Mental Health. Gaps in the literature were identified, including a lack of standard features of historical trauma, and assessments of historical trauma in additional contexts than its original fields of application with Indigenous Americans CONCLUSION: Although the introduction of the concept of historical trauma was intended to fill the gap of trauma-related difficulties not covered by the criteria of post-traumatic stress disorder (PTSD), this concept needs further scientific refinement.

PMID:36716783 | DOI:10.1002/cpp.2836

Intensive Crit Care Nurs. 2023 Jan 25;76:103376. doi: 10.1016/j.iccn.2022.103376. Online ahead of print.

ABSTRACT

OBJECTIVES: To investigate the construct validity and psychometric properties of the Swedish version of the Moral Distress Scale-Revised and to describe moral distress in an intensive care context.

RESEARCH METHODOLOGY/DESIGN: The Italian Moral Distress Scale-Revised was translated and semantically adjusted to the Swedish intensive care context. A web survey with 14 moral distress items, as well as three additional and eight background questions was answered by critical care nurses (N = 71) working in intensive care units during the second year of the coronavirus disease pandemic. Inferential and descriptive statistics were used to investigate the Italian four-factor model and to examine critical care nurses' moral distress.

RESULTS: The result shows a factor model of four components differing from the previous model. Critical care nurses demonstrated significant differences in moral distress regarding priorities compared to before the pandemic, type of household; experience as critical care nurses and whether they had supervised students during the pandemic.

CONCLUSION: The component structure might have originated from the specific situation critical care nurses perceived during the pandemic. The health care organisations' role in preventing and healing the effects of moral distress is important for managers to understand.

IMPLICATIONS FOR CLINICAL PRACTICE: Moral distress is common in intensive care and it is necessary to use valid instrument when measuring it. A psychometrical investigation of the Swedish version of the Moral Distress Scale-Revised, adapted for intensive care shows need for further semantic and cultural adaptation. Perceived priorities during the pandemic, household type, supervising during the pandemic and working experience were related to critical care nurses' experience of moral distress and managers need to be aware of conditions that may trigger such a response.

PMID:36706495 | DOI:10.1016/j.iccn.2022.103376

JMIR Med Inform. 2023 Jan 27;11:e41614. doi: 10.2196/41614.

ABSTRACT

BACKGROUND: The electronic health record (EHR) targets systematized collection of patient-specific, electronically stored health data. The EHR is an evolving concept driven by ongoing developments and open or unclear legal issues concerning medical technologies, cross-domain data integration, and unclear access roles. Consequently, an interdisciplinary discourse based on representative pilot scenarios is required to connect previously unconnected domains.

OBJECTIVE: We address cross-domain data integration including access control using the specific example of a unique device identification (UDI)-expanded hip implant. In fact, the integration of technical focus data into the hospital information system (HIS) is considered based on surgically relevant information. Moreover, the acquisition of social focus data based on mobile health (mHealth) is addressed, covering data integration and networking with therapeutic intervention and acute diagnostics data.

METHODS: In addition to the additive manufacturing of a hip implant with the integration of a UDI, we built a database that combines database technology and a wrapper layer known from extract, transform, load systems and brings it into a SQL database, WEB application programming interface (API) layer (back end), interface layer (rest API), and front end. It also provides semantic integration through connection mechanisms between data elements.

RESULTS: A hip implant is approached by design, production, and verification while linking operation-relevant specifics like implant-bone fit by merging patient-specific image material (computed tomography, magnetic resonance imaging, or a biomodel) and the digital implant twin for well-founded selection pairing. This decision-facilitating linkage, which improves surgical planning, relates to patient-specific postoperative influencing factors during the healing phase. A unique product identification approach is presented, allowing a postoperative read-out with state-of-the-art hospital technology while enabling future access scenarios for patient and implant data. The latter was considered from the manufacturing perspective using the process manufacturing chain for a (patient-specific) implant to identify quality-relevant data for later access. In addition, sensor concepts were identified to use to monitor the patient-implant interaction during the healing phase using wearables, for example. A data aggregation and integration concept for heterogeneous data sources from the considered focus domains is also presented. Finally, a hierarchical data access concept is shown, protecting sensitive patient data from misuse using existing scenarios.

CONCLUSIONS: Personalized medicine requires cross-domain linkage of data, which, in turn, require an appropriate data infrastructure and adequate hierarchical data access solutions in a shared and federated data space. The hip implant is used as an example for the usefulness of cross-domain data linkage since it bundles social, medical, and technical aspects of the implantation. It is necessary to open existing databases using interfaces for secure integration of data from end devices and to assure availability through suitable access models while guaranteeing long-term, independent data persistence. A suitable strategy requires the combination of technical solutions from the areas of identity and trust, federated data storage, cryptographic procedures, and software engineering as well as organizational changes.

PMID:36705946 | DOI:10.2196/41614

J Transl Med. 2023 Jan 25;21(1):48. doi: 10.1186/s12967-023-03876-3.

ABSTRACT

BACKGROUND: Drug-target interaction (DTI) prediction has become a crucial prerequisite in drug design and drug discovery. However, the traditional biological experiment is time-consuming and expensive, as there are abundant complex interactions present in the large size of genomic and chemical spaces. For alleviating this phenomenon, plenty of computational methods are conducted to effectively complement biological experiments and narrow the search spaces into a preferred candidate domain. Whereas, most of the previous approaches cannot fully consider association behavior semantic information based on several schemas to represent complex the structure of heterogeneous biological networks. Additionally, the prediction of DTI based on single modalities cannot satisfy the demand for prediction accuracy.

METHODS: We propose a multi-modal representation framework of 'DeepMPF' based on meta-path semantic analysis, which effectively utilizes heterogeneous information to predict DTI. Specifically, we first construct protein-drug-disease heterogeneous networks composed of three entities. Then the feature information is obtained under three views, containing sequence modality, heterogeneous structure modality and similarity modality. We proposed six representative schemas of meta-path to preserve the high-order nonlinear structure and catch hidden structural information of the heterogeneous network. Finally, DeepMPF generates highly representative comprehensive feature descriptors and calculates the probability of interaction through joint learning.

RESULTS: To evaluate the predictive performance of DeepMPF, comparison experiments are conducted on four gold datasets. Our method can obtain competitive performance in all datasets. We also explore the influence of the different feature embedding dimensions, learning strategies and classification methods. Meaningfully, the drug repositioning experiments on COVID-19 and HIV demonstrate DeepMPF can be applied to solve problems in reality and help drug discovery. The further analysis of molecular docking experiments enhances the credibility of the drug candidates predicted by DeepMPF.

CONCLUSIONS: All the results demonstrate the effectively predictive capability of DeepMPF for drug-target interactions. It can be utilized as a useful tool to prescreen the most potential drug candidates for the protein. The web server of the DeepMPF predictor is freely available at http://120.77.11.78/DeepMPF/ , which can help relevant researchers to further study.

PMID:36698208 | DOI:10.1186/s12967-023-03876-3

BMC Med Inform Decis Mak. 2023 Jan 24;23(1):18. doi: 10.1186/s12911-023-02115-5.

ABSTRACT

BACKGROUND: The lack of interoperability between health information systems reduces the quality of care provided to patients and wastes resources. Accordingly, there is an urgent need to develop integration mechanisms among the various health information systems. The aim of this review was to investigate the interoperability requirements for heterogeneous health information systems and to summarize and present them.

METHODS: In accordance with the PRISMA guideline, a broad electronic search of all literature was conducted on the topic through six databases, including PubMed, Web of science, Scopus, MEDLINE, Cochrane Library and Embase to 25 July 2022. The inclusion criteria were to select English-written articles available in full text with the closest objectives. 36 articles were selected for further analysis.

RESULTS: Interoperability has been raised in the field of health information systems from 2003 and now it is one of the topics of interest to researchers. The projects done in this field are mostly in the national scope and to achieve the electronic health record. HL7 FHIR, CDA, HIPAA and SNOMED-CT, SOA, RIM, XML, API, JAVA and SQL are among the most important requirements for implementing interoperability. In order to guarantee the concept of data exchange, semantic interaction is the best choice because the systems can recognize and process semantically similar information homogeneously.

CONCLUSIONS: The health industry has become more complex and has new needs. Interoperability meets this needs by communicating between the output and input of processor systems and making easier to access the data in the required formats.

PMID:36694161 | DOI:10.1186/s12911-023-02115-5

Psychol Aging. 2023 Mar;38(2):87-102. doi: 10.1037/pag0000721. Epub 2023 Jan 23.

ABSTRACT

Computational research suggests that semantic memory, operationalized as semantic memory networks, undergoes age-related changes. Previous work suggests that concepts in older adults' semantic memory networks are more separated, more segregated, and less connected to each other. However, cognitive network research often relies on group averages (e.g., young vs. older adults), and it remains unclear if individual differences influence age-related disparities in language production abilities. Here, we analyze the properties of younger and older participants' individual-based semantic memory networks based on their semantic relatedness judgments. We related individual-based network measures-clustering coefficient (CC; connectivity), global efficiency, and modularity (structure)-to language production (verbal fluency) and vocabulary knowledge. Similar to previous findings, we found significant age effects: CC and global efficiency were lower, and modularity was higher, for older adults. Furthermore, vocabulary knowledge was significantly related to the semantic memory network measures: corresponding with the age effects, CC and global efficiency had a negative relationship, while modularity had a positive relationship with vocabulary knowledge. More generally, vocabulary knowledge significantly increased with age, which may reflect the critical role that the accumulation of knowledge within semantic memory has on its structure. These results highlight the impact of diverse life experiences on older adults' semantic memory and demonstrate the importance of accounting for individual differences in the aging mental lexicon. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

PMID:36689391 | DOI:10.1037/pag0000721

JMIR Med Inform. 2023 Jan 20;11:e38861. doi: 10.2196/38861.

ABSTRACT

BACKGROUND: There is a variety of libre/free and open-source software (LIFOSS) products for medicine and health care. To support health care and IT professionals select an appropriate software product for given tasks, several comparison studies and web platforms, such as Medfloss.org, are available. However, due to the lack of a uniform terminology for health informatics, ambiguous or imprecise terms are used to describe the functionalities of LIFOSS. This makes comparisons of LIFOSS difficult and may lead to inappropriate software selection decisions. Using Linked Open Data (LOD) promises to address these challenges.

OBJECTIVE: We describe LIFOSS systematically with the help of the underlying Health Information Technology Ontology (HITO). We publish HITO and HITO-based software product descriptions using LOD to obtain the following benefits: (1) linking and reusing existing terminologies and (2) using Semantic Web tools for viewing and querying the LIFOSS data on the World Wide Web.

METHODS: HITO was incrementally developed and implemented. First, classes for the description of software products in health IT evaluation studies were identified. Second, requirements for describing LIFOSS were elicited by interviewing domain experts. Third, to describe domain-specific functionalities of software products, existing catalogues of features and enterprise functions were analyzed and integrated into the HITO knowledge base. As a proof of concept, HITO was used to describe 25 LIFOSS products.

RESULTS: HITO provides a defined set of classes and their relationships to describe LIFOSS in medicine and health care. With the help of linked or integrated catalogues for languages, programming languages, licenses, features, and enterprise functions, the functionalities of LIFOSS can be precisely described and compared. We publish HITO and the LIFOSS descriptions as LOD; they can be queried and viewed using different Semantic Web tools, such as Resource Description Framework (RDF) browsers, SPARQL Protocol and RDF Query Language (SPARQL) queries, and faceted searches. The advantages of providing HITO as LOD are demonstrated by practical examples.

CONCLUSIONS: HITO is a building block to achieving unambiguous communication among health IT professionals and researchers. Providing LIFOSS product information as LOD enables barrier-free and easy access to data that are often hidden in user manuals of software products or are not available at all. Efforts to establish a unique terminology of medical and health informatics should be further supported and continued.

PMID:36662569 | DOI:10.2196/38861

JMIR Form Res. 2023 Jan 19;7:e38831. doi: 10.2196/38831.

ABSTRACT

BACKGROUND: Recommender systems have great potential in mental health care to personalize self-guided content for patients, allowing them to supplement their mental health treatment in a scalable way.

OBJECTIVE: In this paper, we describe and evaluate 2 knowledge-based content recommendation systems as parts of Ginger, an on-demand mental health platform, to bolster engagement in self-guided mental health content.

METHODS: We developed two algorithms to provide content recommendations in the Ginger mental health smartphone app: (1) one that uses users' responses to app onboarding questions to recommend content cards and (2) one that uses the semantic similarity between the transcript of a coaching conversation and the description of content cards to make recommendations after every session. As a measure of success for these recommendation algorithms, we examined the relevance of content cards to users' conversations with their coach and completion rates of selected content within the app measured over 14,018 users.

RESULTS: In a real-world setting, content consumed in the recommendations section (or "Explore" in the app) had the highest completion rates (3353/7871, 42.6%) compared to other sections of the app, which had an average completion rate of 37.35% (21,982/58,614; P<.001). Within the app's recommendations section, conversation-based content recommendations had 11.4% (1108/2364) higher completion rates per card than onboarding response-based recommendations (1712/4067; P=.003) and 26.1% higher than random recommendations (534/1440; P=.005). Studied via subject matter experts' annotations, conversation-based recommendations had a 16.1% higher relevance rate for the top 5 recommended cards, averaged across sessions of varying lengths, compared to a random control (110 conversational sessions). Finally, it was observed that both age and gender variables were sensitive to different recommendation methods, with responsiveness to personalized recommendations being higher if the users were older than 35 years or identified as male.

CONCLUSIONS: Recommender systems can help scale and supplement digital mental health care with personalized content and self-care recommendations. Onboarding-based recommendations are ideal for "cold starting" the process of recommending content for new users and users that tend to use the app just for content but not for therapy or coaching. The conversation-based recommendation algorithm allows for dynamic recommendations based on information gathered during coaching sessions, which is a critical capability, given the changing nature of mental health needs during treatment. The proposed algorithms are just one step toward the direction of outcome-driven personalization in mental health. Our future work will involve a robust causal evaluation of these algorithms using randomized controlled trials, along with consumer feedback-driven improvement of these algorithms, to drive better clinical outcomes.

PMID:36656628 | DOI:10.2196/38831

Knowl Inf Syst. 2023 Jan 7:1-28. doi: 10.1007/s10115-022-01826-x. Online ahead of print.

ABSTRACT

In the last decade, a large number of knowledge graph (KG) completion approaches were proposed. Albeit effective, these efforts are disjoint, and their collective strengths and weaknesses in effective KG completion have not been studied in the literature. We extend Plumber, a framework that brings together the research community's disjoint efforts on KG completion. We include more components into the architecture of Plumber to comprise 40 reusable components for various KG completion subtasks, such as coreference resolution, entity linking, and relation extraction. Using these components, Plumber dynamically generates suitable knowledge extraction pipelines and offers overall 432 distinct pipelines. We study the optimization problem of choosing optimal pipelines based on input sentences. To do so, we train a transformer-based classification model that extracts contextual embeddings from the input and finds an appropriate pipeline. We study the efficacy of Plumber for extracting the KG triples using standard datasets over three KGs: DBpedia, Wikidata, and Open Research Knowledge Graph. Our results demonstrate the effectiveness of Plumber in dynamically generating KG completion pipelines, outperforming all baselines agnostic of the underlying KG. Furthermore, we provide an analysis of collective failure cases, study the similarities and synergies among integrated components and discuss their limitations.

PMID:36643405 | PMC:PMC9823264 | DOI:10.1007/s10115-022-01826-x