🧠
Brain Stroke Prediction CT Scan Image Dataset model by iashiqul
⭐ 23
🧠
Model

Brain Stroke Prediction CT Scan Image Dataset

by iashiqul hf-dataset--iashiqul--brain-stroke-prediction-ct-scan-image-dataset
Nexus Index
23.0 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 55
R: Recency 0
Q: Quality 30
Tech Context
Vital Performance
2.4K DL / 30D
0.0%
Audited 23 FNI Score
Tiny - Params
- Context
2.4K Downloads
Restricted UNKNOWN License
Model Information Summary
Entity Passport
Registry ID hf-dataset--iashiqul--brain-stroke-prediction-ct-scan-image-dataset
License Unknown
Provider kaggle
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_dataset__iashiqul__brain_stroke_prediction_ct_scan_image_dataset,
  author = {iashiqul},
  title = {Brain Stroke Prediction CT Scan Image Dataset Model},
  year = {2026},
  howpublished = {\url{https://free2aitools.com/model/hf-dataset--iashiqul--brain-stroke-prediction-ct-scan-image-dataset}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
iashiqul. (2026). Brain Stroke Prediction CT Scan Image Dataset [Model]. Free2AITools. https://free2aitools.com/model/hf-dataset--iashiqul--brain-stroke-prediction-ct-scan-image-dataset

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download iashiqul/brain-stroke-prediction-ct-scan-image-dataset
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
23.0
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 55
Recency (R) 0
Quality (Q) 30

đŸ’Ŧ Index Insight

FNI V2.0 for Brain Stroke Prediction CT Scan Image Dataset: Semantic (S:50), Authority (A:0), Popularity (P:55), Recency (R:0), Quality (Q:30).

Free2AITools Nexus Index

Verification Authority

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⚠ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

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AI Summary: Based on Kaggle metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-dataset--iashiqul--brain-stroke-prediction-ct-scan-image-dataset
slug
iashiqul--brain-stroke-prediction-ct-scan-image-dataset
source
kaggle
author
iashiqul
license
Unknown
tags
[object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], [object

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

📊 Engagement & Metrics

downloads
2,446
stars
21
forks
0

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