Background/Objectives: The increasing application of artificial intelligence (AI) and machine learning (ML) in health and medicine has attracted a great deal of research interest in recent decades. This study aims to provide a global and historical picture of research concerning AI and ML in health and medicine. Methods: We used the Scopus database for searching and extracted articles published between 2000 and 2024. Then, we generated information about productivity, citations, collaboration, most impactful research topics, emerging research topics, and author keywords using Microsoft Excel 365 and VOSviewer software (version 1.6.20). Results: We retrieved a total of 22,113 research articles, with a notable surge in research activity in recent years. Core journals were Scientific Reports and IEEE Access, and core institutions included Harvard Medical School and the Ministry of Education of the People’s Republic of China, while core countries comprised the United States, China, India, the United Kingdom, and Saudi Arabia. Citation trends indicated substantial growth and recognition of AI’s and ML impact on health and medicine. Frequent author keywords identified key research hotspots, including specific diseases like Alzheimer’s disease, Parkinson’s diseases, COVID-19, and diabetes. The author keyword analysis identified “deep learning”, “convolutional neural network”, and “classification” as dominant research themes. Conclusions: AI’s transformative potential in AI and ML in health and medicine holds promise for improving global health outcomes.

Objective This study aims to shed light on the transformative potential of artificial intelligence (AI) in the early detection and risk assessment of non-communicable diseases (NCDs). Study design Bibliometric analysis. Setting Articles related to AI in early identification and risk evaluation of NCDs from 2000 to 2024 were retrieved from the Scopus database. Methods This comprehensive bibliometric study focuses on a single database, Scopus and employs narrative synthesis for concise yet informative summaries. Microsoft Excel V.365 and VOSviewer software (V.1.6.20) were used to summarise bibliometric features. Results The study retrieved 1745 relevant articles, with a notable surge in research activity in recent years. Core journals included Scientific Reports and IEEE Access, and core institutions included the Harvard Medical School and the Ministry of Education of the People’s Republic of China, while core countries comprised China, the USA, India, the UK and Saudi Arabia. Citation trends indicated substantial growth and recognition of AI’s impact on NCDs management. Frequent author keywords identified key research hotspots, including specific NCDs like Alzheimer’s disease and diabetes. Risk assessment studies demonstrated improved predictions for heart failure, cardiovascular risk, breast cancer, diabetes and inflammatory bowel disease. Conclusion Our findings highlight the increasing role of AI in early detection and risk prediction of NCDs, emphasising its widening research impact and future clinical potential.

Magnetic Resonance Imaging (MRI) is increasingly becoming a cornerstone in modern diagnostic healthcare, offering unparalleled capabilities in stroke, dementia, and cancer screening. Therefore, this study aims to map medical MRI literature affiliated with Arab countries, focusing on publication trends, top journals, author affiliations, study countries, and authors' collaboration, and keyword analysis. The scientific database used is the Scopus database. Microsoft Excel, VOSviewer software, and Biblioshiny for the Bibliometrix R package are the bibliometric tools used in this analysis. A total of 2592 publications were published between 1988 and 2022, with total citations of 22,115. Most of them were original articles (91,7%) and 89.9% were published in traditional journals. The number of total publications exhibited a steady increase over time, whereas total citations showed fluctuations, peaking in 2015 with 1571 citations for publications from that year. The most cited article was authored by Yaseen M. Arabi, receiving 286 citations. Saudi Arabia was the top active country. In addition, the most prolific author was Maha S Zaki, and the most prolific source was the “Egyptian Journal of Radiology and Nuclear Medicine”. The most prolific affiliation was Cairo University. The “multiple sclerosis” and “case report” were the most trending keywords. The analysis revealed a significant growth in MRI research inside Arab countries, as shown by an increase in the total number of publications and international collaborations. Despite these developments, the results of this study suggest that there is still room for MRI research in the Arab region to advance. This can be achieved through increasing international collaboration and multidisciplinary work.

Precision oncology and pharmacogenomics (PGx) intersect in their overarching goal to institute the right treatment for the right patient. However, the translation of these innovations into clinical practice is still lagging behind. Therefore, this study aimed to analyze the current state of research and to predict the future directions of applied PGx in the field of precision oncology as represented by the targeted therapy class of tyrosine kinase inhibitors (TKIs). Advanced bibliometric and scientometric analyses of the literature were performed. The Scopus database was used for the search, and articles published between 2001 and 2023 were extracted. Information about productivity, citations, cluster analysis, keyword co-occurrence, trend topics, and thematic evolution were generated. A total of 448 research articles were included in this analysis. A burst of scholarly activity in the field was noted by the year 2005, peaking in 2017, followed by a remarkable decline to date. Research in the field was hallmarked by consistent and impactful international collaboration, with the US leading in terms of most prolific country, institutions, and total link strength. Thematic evolution in the field points in the direction of more specialized studies on applied pharmacokinetics of available and novel TKIs, particularly for the treatment of lung and breast cancers. Our results delineate a significant advancement in the field of PGx in precision oncology. Notwithstanding the practical challenges to these applications at the point of care, further research, standardization, infrastructure development, and informed policymaking are urgently needed to ensure widespread adoption of PGx.

Objective: This study aimed to assess health-related quality of life (HRQoL) among postpartum women in Jordan and identify the factors that may influence it. Methodology: This study employed a cross-sectional design and was conducted among women who had given birth within the last year, selected through cluster randomization from four primary healthcare centers in Amman. Household resource quality of life was measured on the validated 36-Item Short Form Survey (SF-36), which covers eight domains of health. Descriptive statistics were calculated. Independent t-tests and one-way ANOVA were used to compare mean HRQoL scores across categories of socio-demographic variables (e.g., marital status, income, employment, feeding type). Pearson correlation was used to examine the relationship between age (the only continuous variable) and HRQoL domains. Statistical significance was set at p < 0.05. Results: The physical functioning had the highest HRQoL (62.48 ± 25.19), and the lowest HRQoL (34.59 ± 37.46) was found in role limitations due to physical health and emotional problems (36.37 ± 40.90). Key socio-demographic factors were highly related to HRQoL. Better general health perceptions (p = 0.003) and emotional well-being (p = 0.005) were found to be correlated with higher income. The married women scored much higher in physical functioning (p = 0.015) and emotional well-being (p = 0.013) than divorced women. Infant feeding methods and employment status were also significantly associated with certain domains of HRQoL. Conclusions: Postpartum women in Jordan experience low HRQoL, particularly in the domains related to role limitations. Socio-demographic factors were found to be crucial, wherein marital status and income are specific aspects. This study strongly recommends immediate integration of an appropriate multidimensional support program in postpartum care as an intervention toward improving maternal well-being.