The development of artificial intelligence (AI) has revolutionised the medical system, empowering healthcare professionals to analyse complex nonlinear big data and identify hidden patterns, facilitating well-informed decisions. Over the last decade, there has been a notable trend of research in AI, machine learning (ML), and their associated algorithms in health and medical systems. These approaches have transformed the healthcare system, enhancing efficiency, accuracy, personalised treatment, and decision-making. Recognising the importance and growing trend of research in the topic area, this paper presents a bibliometric analysis of AI in health and medical systems. The paper utilises the Web of Science (WoS) Core Collection database, considering documents published in the topic area for the last four decades. A total of 64,063 papers were identified from 1983 to 2022. The paper evaluates the bibliometric data from various perspectives, such as annual papers published, annual citations, highly cited papers, and most productive institutions, and countries. The paper visualises the relationship among various scientific actors by presenting bibliographic coupling and co-occurrences of the author's keywords. The analysis indicates that the field began its significant growth in the late 1970s and early 1980s, with significant growth since 2019. The most influential institutions are in the USA and China. The study also reveals that the scientific community's top keywords include 'ML', 'Deep Learning', and 'Artificial Intelligence'.
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http://dx.doi.org/10.1177/20552076241258757 | DOI Listing |
BMC Cancer
January 2025
Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Objective: Rapid on-site evaluation (ROSE) of respiratory cytology specimens is a critical technique for accurate and timely diagnosis of lung cancer. However, in China, limited familiarity with the Diff-Quik staining method and a shortage of trained cytopathologists hamper utilization of ROSE. Therefore, developing an improved deep learning model to assist clinicians in promptly and accurately evaluating Diff-Quik stained cytology samples during ROSE has important clinical value.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Pediatric Dentistry and Dental Public Health, Faculty of Dentistry, Cairo University, Cairo, Egypt.
Introduction: Artificial intelligence (AI) applications have increased dramatically across a wide range of domains. Dental students will undoubtedly be impacted by the emergence of AI in dentistry.
Aim: This study aimed to evaluate the knowledge, attitudes, and perceptions of a group of Egyptian dental students toward artificial intelligence.
Pathologie (Heidelb)
January 2025
MVZ Dermatopathologie Duisburg Essen GmbH, Essen, Deutschland.
As in general pathology, digitalization is also inexorably making its way into dermatopathology. This article examines the current state of digitalization in German dermatopathology laboratories based on the authors' own experiences, the current study situation, and a survey of members of the Dermatological Histology Working Group (ADH). Experiences with the establishment of a digital laboratory workflow, artificial intelligence (AI)-based assistance systems, and whole slide images (WSI)-based training programs are discussed.
View Article and Find Full Text PDFNat Biotechnol
January 2025
Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, Magdalenka, Poland.
Purpose Of Review: This review aims to evaluate the impact of artificial intelligence (AI) on cancer health equity, specifically investigating whether AI is addressing or widening disparities in cancer outcomes.
Recent Findings: Recent studies demonstrate significant advancements in AI, such as deep learning for cancer diagnosis and predictive analytics for personalized treatment, showing potential for improved precision in care. However, concerns persist about the performance of AI tools across diverse populations due to biased training data.
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