A bibliometric analysis of the advance of artificial intelligence in medicine

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 12

Published: Feb. 21, 2025

The integration of artificial intelligence (AI) into medicine has ushered an era unprecedented innovation, with substantial impacts on healthcare delivery and patient outcomes. Understanding the current development, primary research focuses, key contributors in AI applications through bibliometric analysis is essential. For this research, we utilized Web Science Core Collection as our main database performed a review literature covering period from January 2019 to December 2023. VOSviewer R-bibliometrix were conduct network visualization, including number publications, countries, journals, citations, authors, keywords. A total 1,811 publications for released across 565 journals by 12,376 authors affiliated 3,583 institutions 97 countries. United States became foremost producer scholarly works, significantly impacting field. Harvard Medical School exhibited highest publication count among all institutions. Journal Internet Research achieved H-index (19), (76), citations (1,495). Four keyword clusters identified, digital health, COVID-19 ChatGPT, precision medicine, public health epidemiology. "Outcomes" "Risk" demonstrated notable upward trend, indicating utilization engaging clinicians patients discuss patients' condition risks, foreshadowing future focal points. Analyzing data allowed us identify progress, focus areas, emerging fields pointing potential directions. Since 2019, there been steady rise related its rapid growth. In addition, reviewed significant pinpoint prominent institutions, academics. Researchers will gain important insights landscape, collaborative frameworks, topics field study. findings suggest directions research.

Language: Английский

Effects of Artificial Intelligence Rehabilitation on Motor ability and Daily living ability of Hemiplegic Patients with Stroke—Meta-Analysis of Randomized Controlled Trials (Preprint)

Published: Feb. 10, 2025

A large number of hemiplegic stroke patients worldwide require rehabilitation. Artificial intelligence (AI) has the potential to conserve human resources and offers broad application prospects. With advancements in medicine technology, AI begun integrating into rehabilitation, providing personalized rehabilitation plans. However, effects on motor daily living abilities remain unclear. Evaluate patients. The Cochrane Library, Web Science, PubMed, Embase, CINAHL, CNKI, VIP, Wanfang databases were systematically searched for randomized controlled trials (RCTs) with stroke. search timeframe was from construction database January 1, 2025. literature screened according nerfing criteria, relevant information extracted, Meta-analysis performed using RevMan5.3 software. 16 studies involving 565 hemiplegia included. showed that, compared conventional more effective improving ability [MD=3.35, 95%CI (1.39, 5.32), P<0.001], balance [MD=7.26, (6.37, 8.14), muscle strength grip [SMD=0.65, (0.25, 1.04), P=0.001], perform activities [SMD=1.71, (0.73, 2.69), P<0.001]. improvements limb function [MD=0.11, (-0.06, 0.28), P=0.210], tone [MD=-0.28, (-0.57, 0.02), P=0.060], [MD=-0.04, (-0.49, 0.41), P=0.860], hand dexterity [MD=9.31, (-7.48, 26.09), P=0.280] not statistically significant. Subgroup analyses revealed no statistical difference between machines [MD=1.80, (-1.37, 4.97), P=0.270]. In contrast, virtual reality [MD=5.07, (4.23, 5.91), brain-computer interface [MD=6.99, (3.06, 10.92), telerehabilitation [MD=0.96, (0.23, 1.68), P=0.010] all significantly improved performance. Additionally, interventions a total frequency ≥20 [MD=4.29, (2.21, 6.36), P<0.001] duration ≥6 weeks [MD=3.73, (1.22, 6.24), P=0.004] effective. intervention ≥10 hours [MD=5.71, (3.02, 8.40), also had better effect improvement. that >10 [SMD=3.18, (1.44, 4.93), ability. can improve hemiplegia. Using reality, interface, is recommended, ,with interventions, hours. activities, recommended enhance function, strength, strength. it does function. be More high-quality are needed validate these findings further. PROSPERO CRD42025636225；https://tinyurl.com/2uc3eac2.

Language: Английский

Artificial Intelligence in the Diagnosis of Neurological Diseases Using Biomechanical and Gait Analysis Data: A Scopus-Based Bibliometric Analysis

Neurology International, Journal Year: 2025, Volume and Issue: 17(3), P. 45 - 45

Published: March 20, 2025

Neurological diseases are increasingly diverse and prevalent, presenting significant challenges for their timely accurate diagnosis. The aim of the present study is to conduct a bibliometric analysis literature review in field neurology explore advancements application artificial intelligence (AI) techniques, including machine learning (ML) deep (DL). Using VOSviewer software (version 1.6.20.0) documents retrieved from Scopus database, included 113 articles published between 1 January 2018 31 December 2024. Key journals, authors, research collaborations were identified, highlighting major contributions field. Science mapping investigated areas focus, such as biomechanical data gait AI methodologies neurological disease Co-occurrence author keywords allowed identification four themes: (a) analysis; (b) sensors wearable health technologies; (c) cognitive disorders; (d) disorders motion recognition technologies. insights demonstrate growing but relatively limited collaborative interest this domain, with only few highly cited documents, journals driving research. Meanwhile, highlights current This offers foundation future provides researchers, clinicians, occupational therapists an in-depth understanding AI’s potentially transformative role neurology.

Language: Английский