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The study aims to enhance the detection and classification of conjunctival eye diseases' severity through the development of ConjunctiveNet, an innovative deep learning framework. This model incorporates advanced preprocessing techniques and utilizes a modified Otsu’s method for improved image segmentation, aiming to improve diagnostic accuracy and efficiency in healthcare settings.

ConjunctiveNet employs a convolutional neural network (CNN) enhanced through transfer learning. The methodology integrates rescaling, normalization, Gaussian blur filtering and contrast-limited adaptive histogram equalization (CLAHE) for preprocessing. The segmentation employs a novel modified Otsu’s method. The framework’s effectiveness is compared against five pretrained CNN architectures including AlexNet, ResNet-50, ResNet-152, VGG-19 and DenseNet-201.

The study finds that ConjunctiveNet significantly outperforms existing models in accuracy for detecting various severity stages of conjunctival eye conditions. The model demonstrated superior performance in classifying four distinct severity stages – initial, moderate, high, severe and a healthy stage – offering a reliable tool for enhancing screening and diagnosis processes in ophthalmology.

ConjunctiveNet represents a significant advancement in the automated diagnosis of eye diseases, particularly conjunctivitis. Its originality lies in the integration of modified Otsu’s method for segmentation and its comprehensive preprocessing approach, which collectively enhance its diagnostic capabilities. This framework offers substantial value to the field by improving the accuracy and efficiency of conjunctival disease severity classification, thus aiding in better healthcare delivery.

This paper aims to present a comprehensive overview of open-access publications by Indian non-profit organizations over the past two decades. The study explores the growth, licensing patterns, citations, authorship patterns and other parameters to understand the scholarly output.

The study involves data collection from OpenAlex scholarly catalog. Data analysis uses OpenRefine, a data carpentry tool, to examine and extract various aspects of scholarly output. A total of 89,149 scholarly outputs from 2004 to 2023 were analyzed using statistical and bibliometric methods.

The findings revealed a positive publication growth trend, with 57.74% open access. Gold OA dominates, with 69.61% of papers in 2023. Licensing patterns reveal that 63.75% of OA papers have licenses. Most papers have multiple authors, with 24.83% of over ten authors receiving 60.12% of citations. “Medknow” is the leading publisher, and “The Indian Journal of Ophthalmology” tops journals. Contributions from repositories like SSRN and PubMed are significant. The study also examines citation patterns across different OA types and identifies the top 30 research areas, emphasizing “Medicine” as the most prevalent.

The identified trends and patterns offer valuable insights for policymakers, researchers and organizations to enhance accessibility and impact. This study stresses sustained efforts for transparency and democratization of knowledge in the non-profit sector.

This study filled a gap in existing research by focusing on Indian non-profits, highlighting their roles and impacts often overlooked in scholarly literature. This study provides insights into the growth of open-access publications and their implications in the non-profit sector.

Artificial intelligence (AI) applications are increasingly used for day-to-day operations in healthcare. Each has a relatively limited scope or task, and several find application in managerial and organizational processes. More and more, AI and machine learning (ML) devices have received US FDA approval in the last decade. This chapter covers the main AI applications in healthcare, with a focus on organizational AI solutions (administrative AI), the main AI developers, their investment and real-world data and case studies in healthcare and other sectors. AI can be applied in resource management and procurement, resource allocation, clinical case management, staff work shift scheduling and handling of emergencies. AI applications are becoming ubiquitous in hospital (e.g. emergency room and operating theatre) and outpatient settings (e.g. ambulatory care and dentistry clinics). Their implementation is expected to bring direct benefits for patient care and satisfaction. This chapter gives a broad definition of AI in healthcare settings, with a focus on administrative applications and their use in case study data.

Cataract, or lens opacification, is a major public health burden accounting for more than half of all blindness worldwide. Plant-based dietary indices provide a unique approach to investigating a modifiable risk for age-related cataracts (ARC). The purpose of this study was to investigate the association between plant-based diet indices and risk of ARC.

This case-control study was conducted on 97 patients with newly diagnosed ARC and 198 healthy people (as a control group) in Iran. Convenience sampling and a food frequency questionnaire were used. Three plant-based dietary indices were used based on the health promoting qualities of food items, the overall plant-based diet index (PDI), healthful plant-based diet index (H-PDI) and unhealthful plant-based diet index (U-PDI) which comprised refined carbohydrates and highly processed foods. The plant-based dietary indices were used to investigate relationships with risk of ARC.

After adjusting for potential covariates, no significant association between a higher adherence to O-PDI and risk of ARC. As well, a higher adherence to H-PDI was inversely associated with the risk of ARC (OR = 0.35,95%CI:0.16–0.78). In contrast, there was a significant positive association between a higher adherence to U-PDI and the risk of ARC (OR = 3.67,95%CI:1.66 – 8.15).

The findings of this study have underscored the potential impact of the quality of plant-based food selections on the likelihood of developing ARC. Therefore, adopting a plant-based diet that is rich in nutrient-dense plant-based foods while being low in unhealthy options may have the potential to reduce the risk of ARC.

In modern healthcare environments, collective leadership within nursing teams serves as a fundamental pillar for providing high-quality patient care. The purpose of this study is to identify the factors to improve the collective leadership among the healthcare practitioners.

Using data collected through an online survey of 417 registered nurses in 12 general hospital in Malaysia, the study uses partial least squares structural equation modeling to test the proposed hypotheses.

The result indicate that the collective leadership is directly driven by team shared vision, team commitment and team collaboration. Finding also shows that team shared vision, team commitment and team collaboration has a positive and significant impact on collective leadership. Finally, this study also revealed that, the team collaboration is the most significance factor that affecting the collective leadership among nurses.

This work contributes to a better understanding on collective leadership, ultimately improving team effectiveness and patient care outcomes.

Health-care organisations face many challenges in delivering safe, high-quality services while experiencing significant pressure to increase productivity and reduce costs. In this context, hospitals have implemented lean six sigma (LSS) programmes to improve their performance. This study aims to explore the application of LSS in three different non-profit Ecuadorian hospitals to comprehend the effectiveness of the methodology under this context.

A multiple-case analysis was performed in four phases: selecting the cases, defining a data collection protocol, performing a within-case analysis of each case and performing a cross-case analysis.

This research found that the LSS application positively impacts hospital performance indicators by reducing service time. The most frequently used tools include the supplier input process output customer diagram, value stream mapping, cause-and-effect diagram, five-why analysis, Gemba walk and paired two-sample test. Lastly, the results show that the most common challenges faced were lack of top management engagement, technical training and data availability.

The study is limited by the constraint of a single Latin American country from which the cases were analysed. Collaboration with external partners, like universities, and government policies promoting training in continuous improvement methodologies are crucial for success. Academic implications stress the importance of integrating soft skills in LSS implementation and engineering education.

This study shows a multiple-case analysis of LSS in a Latin American country highlighting the most commonly used tools, their impact on performance and the challenges of implementing LSS in health-care organisations in non-profit Ecuadorian hospitals.

This paper aims to provide insights into the potential of digital technologies-based innovations for more inclusive healthcare by alleviating the affordability, accessibility and availability barriers to utilization of healthcare services. Also, it aims to provide insights into the potential of digital technologies-based innovations for more inclusive services, broadly.

A conceptual framework is inductively developed by analyzing real-world examples of digital technologies-based innovations for more inclusive healthcare through the lenses of economics of information in digital form and certain characteristics of services.

Concurrent implementation of digital technologies-based healthcare innovations with innovations and/or modifications in service processes can enable greater inclusivity by alleviating the affordability, accessibility and availability barriers to utilization of healthcare services.

Issues relating to inequities in healthcare, as a social problem, are the focus of research at multiple levels (e.g. global, national, regional and local) in several academic disciplines. In relation to the scope of the problems and challenges pertaining to providing quality healthcare to the unserved and underserved segments of society, worldwide, the contribution of the proposed framework to practice is modest. However, by highlighting the promise and potential of digital technologies-based innovations as solutions for alleviating barriers to affordability, accessibility and availability of healthcare services during various stages (prevention, detection, diagnosis, treatment and post-treatment follow-up) with illustrative vignettes and developing a framework, the article offers insights for future research. For instance, in reference to mission-driven social enterprises that operate in the product-market space for inclusive innovations under resource constraints, a resourcefulness-based view of the social enterprise constitutes a potential avenue for theory development and research.

Given the conceptual nature of the article, the implications for practice are limited to cognitive implications. Action implications (instrumental implications or implications for practice) are outside of the scope of the article.

Innovations that are economically viable, environmentally sustainable and socially impactful is one of the important issues of our times.

The proposed framework provides insights into the potential of digital technologies-based innovations for more inclusive healthcare by alleviating the affordability, accessibility and availability barriers in the context of emerging and less developed country markets and base of the pyramid segments of society in these markets.

Healthcare organizations have been facing challenges due to high costs and low efficiency in health services. The growth of costs and losses caused by avoidable mistakes lead to the search for solutions, and Health Lean Management appears as a potential solution to help in solving service quality problems, as well as reducing risks. This study aims to analyse the state of the art in the literature centred on the Lean approach in the context of risk management in healthcare organizations, and to identify new research opportunities, highlighting possible lines of future research.

Following a systematic literature review approach, 51 papers were considered relevant for this research, and reviewed to explore the development of literature in this area.

Based on the results, five main research streams were identified: (1) risk management oriented towards patient safety; (2) risk management oriented towards employee safety; (3) importance of attitudes and behaviours in risk reduction projects; (4) Lean tools used in healthcare risk management and (5) Integration of approaches. Moreover, several shortcomings were identified in literature.

Identified shortcomings represent significant opportunities for further research development.

Many buildings fail to meet user expectations, causing a performance gap. Pre-occupancy evaluation (PrOE) is believed to have the potential to close the gap. It enables designers to obtain end-user feedback in the design phase and improve the design for better performance. However, PrOE implementation faces challenges due to still maturing knowledgebase. This study aims to understand the state-of-the-art knowledge of PrOE, thereby identifying future research needs to advance the domain.

A systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework was conducted. A thorough search in five databases and Google Scholar retrieved 90 articles, with 30 selected for systematic review after eliminating duplicates and irrelevant articles. Bibliometric analyses were performed using VOSviewer and Biblioshiny on the article metadata, and thematic analyses were conducted on their contents.

PrOE is a vehicle for engaging building end-users in the design phase to address the credibility gap caused by the discrepancies between the expected and actual performance of buildings. PrOE has gained limited applications in healthcare, residential, office and educational building design for two broad purposes: design management and marketing. Using virtual reality technologies for PrOE has demonstrated significant benefits. Yet, the PrOE domain needs to mature in multiple perspectives to serve its intended purpose effectively.

This study identifies four knowledge gaps for future research to advance the PrOE domain: (1) developing a holistic PrOE framework, integrating comprehensive performance evaluation criteria, useable at different stages of the design phase and multi-criteria decision algorithms, (2) developing a mixed reality tool, embodying the holistic PrOE framework, (3) formulating a PrOE framework for adaptive reuse of buildings and (4) managing uncertainties in user requirements during the lifecycle in PrOE decisions.

The purpose of this study is to analyze the relationship between academic writing and generative artificial intelligence (AI).

This paper is characterized as exploratory and descriptive, with a qualitative approach. Two approaches were used: the first, a narrative review of the literature with a systematic search from which a data collection stage was carried out using asynchronous interviews by means of an online questionnaire.

The results indicate that generative AI should be seen as a complementary tool for creative and critical academic writing. The data collected also highlighted issues related to academic dishonesty and the new type of plagiarism – plagiarism made possible by technologies – as well as issues of authorship and legitimacy of work carried out with AI and the loss of reflective and critical thinking and creativity.

The considerable increase in resources using AI in all dimensions of human life.

The impact that the use of generative AIs can have on the creation of knowledge and the dissemination of scientific research.

The impact that the use of generative AIs can have on the creation of knowledge and on the dissemination of scientific research.

The need for academia to anticipate the use of AI in academic writing and to incorporate its benefits into this process, especially considering researchers in training.

El objetivo de este artículo es analizar la relación entre la escritura académica y la inteligencia artificial generativa.

Este artículo se caracteriza por ser exploratorio y descriptivo, con un enfoque cualitativo. Se utilizaron dos enfoques: el primero, una revisión narrativa de la literatura con una búsqueda sistemática, a partir de la cual se llevó a cabo una etapa de recogida de datos mediante entrevistas asincrónicas a través de un cuestionario online.

Los resultados indican que la IA generativa debe considerarse una herramienta complementaria para la escritura académica creativa y crítica. Los datos recogidos también pusieron de manifiesto cuestiones relacionadas con la deshonestidad académica y el nuevo tipo de plagio, el plagio posibilitado por las tecnologías, así como cuestiones de autoría y legitimidad del trabajo realizado con Inteligencia Artificial, la pérdida de pensamiento reflexivo y crítico y la creatividad.

La necesidad de que el mundo académico se anticipe al uso de la IA en la escritura académica e incorpore sus ventajas a este proceso, considerando principalmente a los investigadores en formación.

El considerable aumento de los recursos que utilizan la IA en todas las dimensiones de la vida humana.

El impacto que puede tener el uso de las IA generativas en la creación de conocimiento y la difusión de la investigación científica.

El impacto que puede tener el uso de las IA generativas en la creación de conocimiento y la difusión de la investigación científica.

O objetivo deste artigo é analisar a relação entre a redação acadêmica e a inteligência artificial generativa.

Este artigo é caracterizado como exploratório e descritivo, com uma abordagem qualitativa. Foram usadas duas abordagens: a primeira, uma revisão narrativa da literatura com uma busca sistemática, a partir da qual foi realizada uma etapa de coleta de dados usando entrevistas assíncronas por meio de um questionário on-line.

Os resultados indicam que a IA generativa deve ser vista como uma ferramenta complementar para a redação acadêmica criativa e crítica. Os dados coletados também destacaram questões relacionadas à desonestidade acadêmica e ao novo tipo de plágio - o plágio possibilitado pelas tecnologias, bem como questões de autoria e legitimidade do trabalho realizado com a Inteligência Artificial, a perda do pensamento reflexivo e crítico e da criatividade.

A necessidade de a academia antecipar o uso da IA na redação acadêmica e incorporar seus benefícios nesse processo, considerando principalmente pesquisadores em formação.

O aumento considerável de recursos usando IA em todas as dimensões da vida humana.

O impacto que o uso de IAs generativas pode ter sobre a criação de conhecimento e a disseminação de pesquisas científicas.

O impacto que o uso de IAs geradoras pode ter na criação de conhecimento e na disseminação de pesquisas científicas.