Data Sheet 1_Congenital heart disease diagnosis using machine learning: a systematic liter

A systematic literature review and meta-analysis of 432 references on congenital heart disease recognition using machine learning. The paper, authored by Khalil Khan, investigates 74 scholarly works published between 2018 and 2025, highlighting databases, algorithms, applications, and solutions. The dataset is a 58.2 KB PDF document summarizing the review's findings.

Use Cases

• Surveying machine learning algorithms for congenital heart disease detection based on the meta-analysis of 74 works.
• Identifying reported datasets used for congenital heart disease recognition based on the survey of literature.
• Analyzing trends and challenges in applying machine learning to congenital heart disease based on the systematic review methodology.

Strengths

• Systematic review methodology applied to 432 references from leading journals.
• Detailed investigation of 74 scholarly works published between 2018 and 2025.
• Released under a permissive CC-BY-4.0 license.

Limitations

• The primary data is a 58.2 KB PDF summary document, not a raw dataset.
• Row count and column-level documentation for any underlying datasets are unknown.
• The description does not specify the geographic or demographic scope of the studies reviewed.

Provenance

Source

Khalil Khan via figshare

Collection Method

Systematic literature review and meta-analysis of published journal articles.

Time Range

2018 to 2025

Freshness

Last updated 2026-04-21 05:34:08.