Binyi Li

Introduction: This study presents a reproducible echocardiographic feature-engineering and machine-learning pipeline for classifying a left ventricular ejection fraction (LVEF)-derived surrogate dysfunction label, using publicly available two-dimensional echocardiographic tracings. The work is explicitly framed as a methodological proof-of-concept rather than a clinically validated model for predicting anthracycline-related right ventricular cardiotoxicity. Methods: A derivative dataset comprising 10,930 records was assembled from the EchoNet-Dynamic database and a CAMUS-derived frame-mask archive. From this pool, a stratified 1,000-record working sample was extracted to support auditable and transparent model development. After mutual-information ranking performed within the training folds, twelve geometric and morphometric features were retained, including left ventricular trace-area change, bounding-box area change, and cohort-median-normalized calibration variables-these were deliberately designed for later substitution with age- and sex-specific Chinese reference values from the EMINCA-II study. Five classifiers were trained using an 800/200 stratified split, with five-fold cross-validation applied inside the training set. Results: Among the five classifiers, logistic regression achieved the highest held-out ROC-AUC of 0.996 and F1 score of 0.966. However, these performance metrics reflect the geometric coupling between the engineered left-ventricular features and the LVEF-derived label, rather than independent clinical predictive capability. A descriptive mediation analysis further showed that the association between bounding-box area change and the dysfunction label was largely transmitted through left ventricular trace-area change. Discussion: The available public data do not include information on anthracycline exposure, Chinese patient identity, right ventricular functional outcomes, or prospective cardiotoxicity endpoints. Therefore, the primary contribution of this study is a transparent, calibration-ready analytical scaffold that can be reused and extended in future prospective Chinese anthracycline cohorts that incorporate true right ventricular outcome measures.

To retrospectively evaluate the efficacy and safety of ultrasound-guided microwave (MWA), radiofrequency (RF), and high-intensity focused ultrasound (HIFU) ablation in the treatment of uterine leiomyoma and to provide a suggestion for the selection of clinical treatment of uterine leiomyoma. The retrospective cohort studies on the efficacy of high-intensity focused ultrasound in treating uterine leiomyoma was collected through a literature search in Pubmed, Embase, Cochrane library, Scopus, and Web of Science, and selected according to the specified inclusion criteria and exclusion criteria. Evaluate the study quality, extract relevant data, and RevMan 5.4.1 was used to conduct this meta-analysis. Compared with HIFU therapy, the complete or partial ablation rate and recurrence rate of uterine leiomyoma treated with RFA/MWA were statistically different (P < 0.05). Compared with RF, the overall efficacy of HIFU in treating uterine leiomyoma was not as good as that of RF. There was no significant difference between the RFA therapy and the MWA. HIFU still has mild and short-term complications, such as abdominal pain, bloody vaginal discharge, sacral pain, and fever. Although myomectomy is usually the first choice for uterine preservation, RFA/MWA and HIFU have also been shown to relieve clinical symptoms significantly, shorten treatment time, reduce complications, and improve prognosis.