Global Trends of Artificial Intelligence Applications in Family Medicine: A Comprehensive Scopus-Based Bibliometric Analysis (2016–2026)

Aim: To map recent artificial intelligence research in family medicine and primary care against an earlier 2015–2024 bibliometric baseline. Methods: Scopus was searched on 9 July 2026 for 2016–2026 publications. One researcher screened 3452 articles and reviews; 132 topical and 13 language exclusions left 3307 records. Manual title, DOI, and Scopus-identifier checks identified no duplicates. VOSviewer 1.6.21 and Biblioshiny (Bibliometrix 5.4.1; R 4.6.1) supported descriptive analysis and mapping. Results: Output increased from 531 in 2024 to 792 in 2025 (49.2%). The 2025 and partial 2026 component contained 1407 records (42.5%); 615 were dated 2026. The USA led publication and raw citation rankings (711 publications; 18,671 citations), while China preceded the United Kingdom in publication count. The Journal of Medical Internet Research (78 publications) and Scientific Reports (69) led the venues; seven top ten venues were shared with the earlier study. Language model terminology coexisted with later-positioned explainability, risk stratification, and diagnostic accuracy terms. Conclusions: This updated map quantifies post-2024 activity and identifies continuity and corpus-dependent differences in geography, dissemination, and evaluation-related vocabulary. Single-database and English language coverage, single-researcher screening, unadjusted citations, and incomplete 2026 coverage limit inference. The findings describe research activity, not clinical adoption, safety, effectiveness, or causality.

Authors

Institutions

Publication Details

Journal
Healthcare
Published
2026-10-26
DOI
https://doi.org/10.3390/healthcare14213611
Primary Topic
scientometrics and bibliometrics research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Global Trends of Artificial Intelligence Applications in Family Medicine: A Comprehensive Scopus-Based Bibliometric Analysis (2016–2026)

Ömer Adil İlhan, Muhammed Fatih Baran
Healthcare
scientometrics and bibliometrics research
article

Global Trends of Artificial Intelligence Applications in Family Medicine: A Comprehensive Scopus-Based Bibliometric Analysis (2016–2026)

Ömer Adil İlhan, Muhammed Fatih Baran
article en

Abstract

Aim: To map recent artificial intelligence research in family medicine and primary care against an earlier 2015–2024 bibliometric baseline. Methods: Scopus was searched on 9 July 2026 for 2016–2026 publications. One researcher screened 3452 articles and reviews; 132 topical and 13 language exclusions left 3307 records. Manual title, DOI, and Scopus-identifier checks identified no duplicates. VOSviewer 1.6.21 and Biblioshiny (Bibliometrix 5.4.1; R 4.6.1) supported descriptive analysis and mapping. Results: Output increased from 531 in 2024 to 792 in 2025 (49.2%). The 2025 and partial 2026 component contained 1407 records (42.5%); 615 were dated 2026. The USA led publication and raw citation rankings (711 publications; 18,671 citations), while China preceded the United Kingdom in publication count. The Journal of Medical Internet Research (78 publications) and Scientific Reports (69) led the venues; seven top ten venues were shared with the earlier study. Language model terminology coexisted with later-positioned explainability, risk stratification, and diagnostic accuracy terms. Conclusions: This updated map quantifies post-2024 activity and identifies continuity and corpus-dependent differences in geography, dissemination, and evaluation-related vocabulary. Single-database and English language coverage, single-researcher screening, unadjusted citations, and incomplete 2026 coverage limit inference. The findings describe research activity, not clinical adoption, safety, effectiveness, or causality.

HealthcareVol. 14(21)
Konya Numune Hastanesi (TR), Konya Eğitim ve Araştırma Hastanesi (TR), Konya City Hospital (TR), Konya Meram State Hospital (TR)
Openalex Percentile: Top 11%
scientometrics and bibliometrics research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
Global Trends of Artificial Intelligence Applications in Family Medicine: A Comprehensive Scopus-Based Bibliometric Analysis (2016–2026) — Ömer Adil İlhan, Muhammed Fatih Baran · Healthcare (2026) | TGRS Research Map | TGRS