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This study aims to delve into the role that telehealth plays in mitigating health inequities faced by forcibly displaced Ukrainians amidst the ongoing conflict.

A retrospective cross-sectional study design was implemented, using data procured from the electronic health records of the Likarnya online project. The research approach integrated descriptive statistics, visual data representations and inferential analyses, including chi-square tests, odds ratio calculations and logistic regression tests.

The analysis revealed a predominance of female users (77.1%) and a high prevalence of health-care access barriers (69.7%). General practice/internal medicine consultations constituted the majority of referrals (72.93%), with a notable 78.66% of cases achieving closure. A significant prevalence rate was observed concerning chronic conditions relative to acute presentations. Statistical analyses uncovered significant associations between case severity and health-care access barriers, with moderate and severe cases demonstrating elevated odds of encountering obstacles to care. Age emerged as a crucial predictor of health-care access difficulties, highlighting the particular vulnerabilities faced by older displaced individuals.

This study highlights the potential of telemedicine in reducing health-care access disparities of displaced populations in conflict zones. Furthermore, this study brings to light pivotal insights concerning demographic and clinical variables that influence patterns associated with health-care services attainability. These findings serve as a clarion call for targeted interventions explicitly tailored for older individuals and those with severe health conditions. Hence, the findings provide a foundation upon which forthcoming academic endeavours alongside strategic policy formulation may be constructed.

The ranking of universities and other research-intensive institutions in global ranking systems is based on numerous indicators, including number of articles with external collaboration, number of articles with international collaboration, number of articles with industry collaboration as well as co-patents with industry. The purpose of this paper is to examine university–industry research collaboration in Ghana, with the aim of exploring the relationship between the research output collaborations in the top four universities in Ghana and industry across different geographical scales.

This study’s data was obtained from the SciVal database, which drawn its data from the Scopus bibliographic and citation database. The bibliographic and citation data were extracted using a search of the publications affiliated to the University of Ghana, for the period 2011–2020.

Key findings demonstrate a constant rise in the number of research publications by the selected universities over time. Research collaboration intensity in the selected universities in terms of co-authored publications was higher as compared to single-authored publications. University–industry research co-authorships were, however, lower when compared to university–university research co-authorships. The university–industry research co-authorships occurred mostly with Europe, Asia-Pacific and North American-based institutions as opposed to African-based institutions. In Ghana, four industry-based institutions were engaged in intensive research with the selected universities.

This study demonstrates that, for each selected university, it is possible to measure the performance of individual universities in both intra-regional and international collaboration. Such results may be useful in informing policy as well as merit-based public funding of universities in Ghana.

The paper faces artificial intelligence issues in the venture creation process, exploring how artificial intelligence solutions intervene and forge the venture creation process. Drawing on the most recent literature on artificial intelligence and entrepreneurship, the authors propose a set of theoretical propositions.

The authors adopt a multiple case approach to assess propositions and analyse 4 case studies from which the authors provide (1) more detailed observation about entrepreneurial process phases influenced by artificial intelligence solutions and (2) more details about mechanics enabled by artificial intelligence.

The analysis demonstrates artificial intelligence contributes alongside the entrepreneurial process, enabling mechanisms that reduce costs or resources, generate new organizational processes but simultaneously expand the network needed for venture creation.

The paper adopts a deductive approach analyzing the contribution of AI-based startup offerings in changing the entrepreneurial process. Thus, the paper provides a practical view of the potentiality of artificial intelligence in enabling entrepreneurial processes through the analysis of compelling propositions and the technological ability of artificial intelligence solutions.