Artificial Intelligence for Predicting Perioperative Outcomes in Cardiac Surgery: A Systematic Review
Jason Ha, Hunaid A Vohra · 2026
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Description
Jason Ha and Hunaid Vohra reviewed in 2026 the use of artificial intelligence to predict outcomes around heart surgery. Heart surgery carries real risk of complications and death, so better risk forecasts could guide care. The team gathered studies from recent years that used AI models for this purpose.
Most included studies were from the United States or China and looked back at past data. The most common methods were random forests, logistic regression, and gradient boosting. Models were used mainly to predict complications after surgery and death, and they usually beat classic risk scores. Few studies checked their models on outside data or followed reporting guidelines. The authors urge better validation before clinical use.
Catalog record
| CREATOR | Jason Ha, Hunaid A Vohra |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 29 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |