AI-Assisted Diagnostic Tool Performance for Schistosoma Haematobium Detection

Sisay Desale's dataset on figshare, last updated May 5, 2026, compiles characteristics and diagnostic performance metrics from studies on AI-assisted tools for detecting Schistosoma haematobium. The dataset is a 9.5 KB XLS file. It likely contains tabular data summarizing study methodologies and performance results.

Use Cases

• Benchmarking AI model performance for Schistosoma haematobium detection based on reported diagnostic metrics.
• Analyzing study design characteristics and their correlation with diagnostic accuracy.
• Conducting meta-analyses of AI-assisted diagnostic tools in parasitology.
• Identifying research gaps in the application of AI for neglected tropical disease diagnostics.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• File size of 9.5 KB indicates a focused, manageable compilation.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Sisay Desale via figshare.

Collection Method

Likely compiled from a systematic review or meta-analysis of published studies.

Freshness

Last updated 2026-05-05 17:36:48; freshness should be verified.