A p53 score derived from TP53 CRISPR/Cas9 HMCLs predicts survival and reveals major role of BAX in BH3 mimetics response

NIAID Data Ecosystem2026-05-01 收录

多发性骨髓瘤生存预测

BH3模拟物响应机制

数据链接：

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE245163 数据链接链接失效反馈

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资源简介：

This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

创建时间：

2024-04-05

Table_2_Machine Learning–Based Overall Survival Prediction of Elderly Patients With Multiple Myeloma From Multicentre Real-Life Data.docx

多发性骨髓瘤生存预测

机器学习预后模型

ObjectiveTo use machine learning methods to explore overall survival (OS)-related prognostic factors in elderly multiple myeloma (MM) patients. MethodsData were cleaned and imputed using simple imputa

NIAID Data Ecosystem50

Table_1_Machine Learning–Based Overall Survival Prediction of Elderly Patients With Multiple Myeloma From Multicentre Real-Life Data.docx

多发性骨髓瘤生存预测

老年患者预后建模

NIAID Data Ecosystem20

Reproducibility package for dynamic-t multimodal landmark survival prediction in multiple myeloma: MMRF CoMMpass, external validation, and training outputs

多发性骨髓瘤生存预测

多模态临床预后建模

This Figshare item contains the reproducibility package for a dynamic-t multimodal landmark survival prediction framework for multiple myeloma. The codebase supports multimodal survival modeling using

NIAID Data Ecosystem00

DataSheet_1_Socioeconomic status-based survival disparities and nomogram prediction for patients with multiple myeloma: Results from American and Chinese populations.pdf

多发性骨髓瘤生存预测

社会经济因素与癌症预后

ObjectiveThis study aimed to comprehensively investigate the relationship between the survival differences and socioeconomic status (SES) in patients with multiple myeloma (MM) and construct a predict

NIAID Data Ecosystem40

Reproducibility package for dynamic-t multimodal landmark survival prediction in multiple myeloma: MMRF CoMMpass, external validation, and training outputs

多发性骨髓瘤生存预测

生存建模

Figshare2026-03-18 更新10