March 3, 2026Open Access

Ceramide-based machine learning models for the diagnosis of unstable angina: a prospective multicenter study

Key Points

The machine learning model effectively diagnoses unstable angina, enhancing clinical efficacy.
Combining ceramide with conventional clinical variables shows promising diagnostic accuracy for unstable angina.

Structured PICO

Does a machine learning model combining ceramide and conventional clinical variables effectively diagnose unstable angina?

Population

Patients evaluated for unstable angina

Intervention

Machine learning model combining ceramide and conventional clinical variables

Outcome

Diagnosis of unstable angina

A ceramide-based machine learning model combined with clinical variables effectively diagnoses unstable angina.

Abstract

The machine learning model combining ceramide and conventional clinical variables effectively diagnoses UA, improving clinical efficacy. Future studies will validate and refine this model through expanded multicenter research.

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