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The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

This study aims to examine the relationship between the chemical composition of juices obtained from fruits of autochthonous wild pomegranate (Punica granatum L.) grown in Montenegro and their cytotoxic effects on cancer cells.

To explore the potential value of wild pomegranate fruits, in vitro biological assays were carried out with juices whose composition was analyzed in detail for sugars, organic acids, vitamin C and phenolic compounds. The effect of juices on survival was determined in human lung A549, cervical HeLa and breast MCF-7 carcinoma cells by MTT assay. As a control, the cytotoxicity against normal fetal lung fibroblasts (MRC-5) was monitored.

Among cancer cell lines, considering the IC50 related to total phenolics, the lowest value – 13 µg/mL was found for the A549. The strongest effect on lung cells was assumed due to the favorable contribution of ellagitannins to total phenolics in juice as well as the given combination of anthocyanins and their synergistic action. For HeLa cells, the lowest IC50 value was obtained at 88 µg/mL, and the cytotoxicity could be matched with the effects of anthocyanins and catechin. For MCF-7 cells, the lowest IC50 was 504 µg/mL, and the elevated levels of vitamin C and ellagic acid derivatives should have a noticeable effect on these cells.

This study provides an important contribution to the knowledge on the effect of phytochemicals from wild pomegranate juice on lung, cervical and breast cancer cells, in vitro. The present observations suggest that the juice of wild pomegranate has the potential in the fight against cancer.

This study aimed to evaluate the compositional changes and bioaccessibility of phenolics and antioxidants in propolis during in vitro digestion as well as the cytotoxic effects of digested propolis on various cancer cell lines.

Six propolis samples were obtained and subjected to in vitro oral, gastric and intestinal digestion. Both digested and undigested samples were analyzed for their total phenolic, flavonoid and antioxidant activities. Additionally, changes in phenolic composition in the in vitro digestion system were revealed by the HPLC-DAD system. The cytotoxic effects of the digested samples were assessed on lung (A549, H1299), skin (A431), liver (Hep-G2) and colon (Caco-2) cancer cells as well as on fibroblast (Bj) cells.

The mean bioaccessibility values of phenolic and flavonoid compounds were found to be less than 35 and 24%, respectively, while the TEAC and CUPRAC antioxidant results ranged between 225.08–649.04 and 398.68–1552.28 µmol TE/g, respectively. The release of p-coumaric, ferulic, 3,4-dimethoxycinnamic acids, naringenin, pinocembrin and chrysin increased progressively from the oral to the intestinal stage. The cytotoxic effects of samples on cell lines were ranked, based on IC50 results, as A431 > Hep-G2 > Caco-2 > A549 > H1299 > Bj.

Propolis has been recognized for centuries as a natural remedy, and numerous studies have explored its bioactive components. However, no studies have previously examined the changes in the phenolic compositions of propolis samples during digestion or their cytotoxic effects on cancer cells. Therefore, this study provides novel insights and an approach to the existing literature on this topic.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

This paper aims to critically review the isolation and chemistry of plant pigments.

A literature survey from 1974 to 2022 was carried out and studied thoroughly. The authors reviewed literature in various areas such as isolation methods and catalytic properties of pigments.

With vast growing research in the field of catalytic activities of various pigments like chlorophyll, anthocyanin and flavonoids, there is still scope for further research for the pigments such as Lycopene, carotenoids and xanthophyll as there has not been any significant work in this area.

Plant pigments may be used as an ecofriendly catalyst for chemical reactions.

One can get the direction of pigment research.

Plant pigments are natural and ecofriendly catalyst which can reduce the pollution.

This is an original work. This paper precisely depicts the advantages as well as disadvantages of the isolation techniques of pigments. This study also presents the chemistry of plant pigments.

Nurses are capable of acting as advocates for patients since they hold valuable knowledge on patient preferences and their psychosocial needs. Yet, in practice they tend to contribute little to multidisciplinary team meetings (MDTMs). This study analyses the factors that influence whether or not nurses will speak up and increase patient-centred decision-making in MDTMs.

A multiple case study with cross-case comparison of twelve tumour groups across two Belgian hospitals was conducted. Data collection involved fifty structured non-participant observations and 41 semi-structured interviews with participants from the twelve tumour groups.

This study yields factors that increase the opportunities for nurses to speak up in MDTMs to enhance patient-centred decision-making. The findings help in the design of future interventions concerning multidisciplinary teamwork, that address nurses’ contributions to augment patient-centred care.

Augmented reality (AR) is an advanced version of the dynamic physical space that is perceived and received via visual, audio, digital and other sensory stimuli. The capabilities of virtual technologies change the field of university and education considerably. The necessity of using virtual technologies in the education field was revealed more in unforeseen disasters such as the COVID-19 pandemic. The adoption of a technology by its users is an important factor in the successful implementation of the technology. The present study evaluates several factors affecting the adoption of AR technology in the realm of tertiary education.

This study is applied in nature, and the necessary data were gathered through a survey questionnaire. The opinions of 621 students were investigated using a simple random sampling method. The multinomial logit test was used in this research.

It was found that individual and social factors such as age, education level, major and economic characteristics such as one’s income in a month, expenses of a person in a month, the level of access to high-speed internet and access to a laptop or smartphone are effective in AR technology adoption in the field of academic education.

The theoretical contribution of this study is to identify the key factors that influence the adoption of AR technology and develop a model specifically applicable to the educational field. The results of this research can be used by university managers and educational policymakers for the efficient and effective use of this technology.

This research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.

A total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.

The People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.

This study helps librarians, scientists and funders understand smart library trends.

There are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.

This systematic review aimed to identify and categorize applications using Fast Healthcare Interoperability Resources (FHIR) to support activities outside of direct healthcare provision.

A systematic electronic search was performed, and 53 studies were included after the selection process.

The results show that FHIR is being used to support (1) clinical research (i.e. clinical research based on interventional trials, data interoperability to support clinical research and advanced communication services to support clinical research), (2) public health and (3) medical education. Despite the FHIR potential to support activities outside of direct healthcare provision, some barriers were identified, namely difficulties translating the proposed applications to clinical environments or FHIR technical issues that require further developments.

This study provided a broad review of how FHIR is being applied in clinical activities outside of direct clinical care and identified three major domains, that is, clinical research, public health and medical education, being the first and most representative in terms of number of publications.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.