Explainability of Logistic Regression model with SHAP method and the online tool for forecasting distant metastasis in patients with gastric cancer.

<p>(A) The bar plot by SHAP. (B) The dot plot by SHAP. (C) The online tool for forecasting distant metastasis in patients with gastric cancer. Abbreviations: TMI: toumor marker index; PLR: Platelet-to-lymphocyte ratio.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Shaoxue Yang (9517160) (author)
مؤلفون آخرون:	Han Lei (417024) (author)
منشور في:	2025
الموضوعات:	Biochemistry Molecular Biology Developmental Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified zhejiang provincial hospital ten laboratory indicators shapley additive explanations retrospectively analyzed 1 logistic regression emerged high mortality rates edited nearest neighbors driven risk stratification borderline synthetic minority among five models 922 &# 8211 897 &# 8211 867 &# 8211 843 &# 8211 833 &# 8211 926 ), respectively zhejiang cancer hospital guide preoperative decision external test cohort optimal predictive model identified key metastasis 009 gc patients 962 ), recall nine clinical features xlink "> univariate shap analysis revealed xlink "> 947 ), preoperative prediction identified features gastric cancer distant metastasis development cohort clinical features significant role sampling technique sampling method related features predictions made online tool necessitating advancements multivariate analyses management strategies machine learning highest area feature importance early detection differentiation grade ct stage composite indices
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

كن أول من يترك تعليقا!

Explainability of Logistic Regression model with SHAP method and the online tool for forecasting distant metastasis in patients with gastric cancer.

مواد مشابهة