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Health Sciences › Health Professions › Health Information Management
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone
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Paper Summary
Conflicts of Interest
Identified Weaknesses
Rating Explanation
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Paper Summary
Paperzilla title
Two Blood Tests Are All You Need to Predict Heart Failure Survival (Probably)
This study found that machine learning models, trained on only serum creatinine and ejection fraction, can accurately predict the survival of heart failure patients. These two factors alone outperformed models using all available clinical features, highlighting their potential importance in clinical practice.
Possible Conflicts of Interest
None identified
Identified Weaknesses
Small dataset size
The dataset employed is small (299 patients). A larger dataset would have led to more robust and reliable results.
Lack of detailed patient information
The dataset lacks additional information about patients' physical features and occupational history, potentially limiting the identification of further relevant risk factors.
No external validation set
The study lacks an external validation set from a different geographic region, which limits the ability to thoroughly assess the generalizability of the findings.
Rating Explanation
The study uses a rigorous methodology, applying diverse machine learning techniques to a real-world medical dataset. Cross-validation and exploration of feature importance strengthen the findings. The limitations around dataset size and lack of broader validation prevent a 5-star rating.
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Topic Hierarchy
File Information
Original Title:
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone
File Name:
s12911-020-1023-5.pdf
[download]
File Size:
0.92 MB
Uploaded:
July 14, 2025 at 11:19 AM
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