A machine learning model for predicting ischemic and bleeding risk after percutaneous coronary intervention: Development and external validation
Hassa Iftikhar, Chiara Lazzeri, Chiara Lazzeri, Chiara Lazzeri · 2026
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Description
Hassa Iftikhar builds a machine learning model that forecasts clot and bleeding risk after heart stent procedures in a 2026 paper. Patients on dual blood thinners after stenting walk a line between clots and bleeds. A gradient boosting model trained on a United Arab Emirates cohort of nearly five thousand patients.
Checked abroad on an American intensive care database, the model kept strong accuracy for both harms. It beat the standard DAPT and PRECISE-DAPT scores at telling future cases from safe patients. Trial runs of risk-guided care suggested savings as well as safety. The author presents the tool for bedside testing next.
Catalog record
| CREATOR | Hassa Iftikhar, Chiara Lazzeri, Chiara Lazzeri, Chiara Lazzeri |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 94 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |