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Article History

Received: 21 October 2025

Accepted: 27 February 2026

First Online: 2 April 2026

Declarations

:

: The study adhered to the principles outlined in the Declaration of Helsinki and received approval from the Human Ethics Review Committee of the First Affiliated Hospital of Chongqing Medical University (reference number: K2023–314). The ethics review board granted an exemption from obtaining informed consent due to the retrospective nature of the study. Patient records were collected and analyzed with strict measures to maintain the confidentiality of participants’ identities, thereby ensuring the protection of patient privacy.

: Not applicable.

: In this study, machine learning algorithms (Random Forest, XGBoost, Logistic Regression, Naive Bayes, Gradient Boosting, SVM) were employed to develop a predictive model for distinguishing invasive fungal from bacterial infections in multiple myeloma patients. No LLMs (e.g., ChatGPT) were used for manuscript preparation.

: The authors declare no competing interests.