Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer
PurposeThe purpose of this study was to investigate the clinical and non-clinical characteristics that may affect the early death rate of patients with metastatic colorectal carcinoma (mCRC) and develop accurate prognostic predictive models for mCRC.MethodMedical records of 35,639 patients with mCRC...
Saved in:
Main Authors: | Yalong Zhang (Author), Zunni Zhang (Author), Liuxiang Wei (Author), Shujing Wei (Author) |
---|---|
Format: | Book |
Published: |
Frontiers Media S.A.,
2022-12-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Construction and validation of a nomogram for predicting survival in elderly patients with cardiac surgery
by: Tonghui Xie, et al.
Published: (2022) -
Construction and Validation of a Nomogram Model to Predict the Severity of Mycoplasma pneumoniae Pneumonia in Children
by: Li L, et al.
Published: (2024) -
EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer
by: Leila Mirsadeghi, et al.
Published: (2021) -
Development and validation of a nomogram to predict intracranial haemorrhage in neonates
by: Shuming Xu, et al.
Published: (2024) -
Dynamic Nomogram Based on the Metastatic Number and Sites and Therapy Strategies Predicting the Prognosis of Patients with Metastatic Cervical Cancer
by: Ma Y, et al.
Published: (2022)