
This repository contains the complete analytical pipeline used in the study “Artificial Intelligence Applications in Cardiovascular Research in Indonesia: A Bibliometric, Thematic, and Trend Analysis (2015–2025)”.The project applies natural language processing (NLP) and unsupervised machine learning techniques to systematically explore research themes, temporal trends, and future directions of AI-driven cardiovascular studies involving Indonesian research contexts. All scripts, preprocessing steps, clustering procedures, and visualisation outputs are provided to ensure full transparency, reproducibility, and methodological rigor, in line with PRISMA 2020 and open science principles.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
