Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system

Z Zhang, L Huang, J Li, P Wang - BMC bioinformatics, 2022 - Springer
Objectives Immune microenvironment was closely related to the occurrence and
progression of colorectal cancer (CRC). The objective of the current research was to …

Mean lifetime survival estimates following solid organ transplantation in the US and UK

CN Graham, C Watson, A Barlev… - Journal of Medical …, 2022 - Taylor & Francis
Aims Accurately estimating mean survival after solid organ transplant (SOT) is crucial for
efficient healthcare resource allocation decisions. However, registry-based post-transplant …

A Machine Learning–Based Risk Score for Prediction of Infective Endocarditis Among Patients With Staphylococcus aureus Bacteremia—The SABIER Score

CKC Lai, E Leung, Y He, C Ching-Chun… - The Journal of …, 2024 - academic.oup.com
Background Early risk assessment is needed to stratify Staphylococcus aureus infective
endocarditis (SA-IE) risk among patients with S. aureus bacteremia (SAB) to guide clinical …

Development and validation of a multivariate predictive model for rheumatoid arthritis mortality using a machine learning approach

JM Lezcano-Valverde, F Salazar, L León, E Toledano… - Scientific reports, 2017 - nature.com
We developed and independently validated a rheumatoid arthritis (RA) mortality prediction
model using the machine learning method Random Survival Forests (RSF). Two …

Random survival forest for predicting the combined effects of multiple physiological risk factors on all-cause mortality

B Zhao, VK Nguyen, M Xu, JA Colacino, O Jolliet - Scientific Reports, 2024 - nature.com
Understanding the combined effects of risk factors on all-cause mortality is crucial for
implementing effective risk stratification and designing targeted interventions, but such …

[HTML][HTML] A machine learning method for improving liver cancer staging

Z Zhao, Y Tian, Z Yuan, P Zhao, F Xia, S Yu - Journal of Biomedical …, 2023 - Elsevier
Liver cancer is a common malignant tumor, and its clinical stage is closely related to the
clinical treatment and prognosis of patients. Currently, the BCLC staging system revised by …

Application of random survival forests in understanding the determinants of under-five child mortality in Uganda in the presence of covariates that satisfy the …

JB Nasejje, H Mwambi - BMC research notes, 2017 - Springer
Background Uganda just like any other Sub-Saharan African country, has a high under-five
child mortality rate. To inform policy on intervention strategies, sound statistical methods are …

PRMT: predicting risk factor of obesity among middle-aged people using data mining techniques

R Hossain, SMH Mahmud, MA Hossin… - Procedia computer …, 2018 - Elsevier
Obesity is an anatomical condition characterized by an extreme growth of body fat. The
obesity rate is increasing gradually; from prior research, obesity is the serious health …

[HTML][HTML] AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data

F Xie, Y Ning, H Yuan, BA Goldstein, MEH Ong… - Journal of Biomedical …, 2022 - Elsevier
Background Scoring systems are highly interpretable and widely used to evaluate time-to-
event outcomes in healthcare research. However, existing time-to-event scores are …

Risk prediction of dyslipidemia for Chinese Han adults using random Forest survival model

X Zhang, F Tang, J Ji, W Han, P Lu - Clinical epidemiology, 2019 - Taylor & Francis
Objective Dyslipidemia has been recognized as a major risk factor of several diseases, and
early prevention and management of dyslipidemia is effective in the primary prevention of …