Back to search

Article

Heterogeneity and risk prediction study of self-reported outcomes in patients with abdominal wall stoma for bladder cancer based on latent profile analysis and machine learning algorithms

2024-12-05

Abstract excerpt

<title>Abstract</title> <p>Abdominal wall stomas in bladder cancer patients can severely impact physical, psychological, and social adjustment. However, individual differences in patients' self-reported outcomes and their influencing factors require further investigation. This multicenter, cross-sectional study aimed to assess the health status of patients with bladder cancer and abdominal wall stomas, identify h...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
9e04f9fa-9e8e-540f-8c3b-a8b45c9ce5d4
DOI
10.21203/rs.3.rs-5316017/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Heterogeneity and risk prediction study of self-reported outcomes in patients with abdominal wall stoma for bladder cancer based on latent profile analysis and machine learning algorithmsDOI 10.21203/rs.3.rs-5316017/v1
Machine Learning and Latent Profile Analysis Predict the Health-Related Quality of Life of Bladder Cancer Patients with Abdominal Wall StomasSemantic proximity
Construction and Validation of a Machine Learning-Based Prediction Model for Social Isolation in Patients with Colorectal Cancer after Stoma SurgerySemantic proximity
Establishment and Validation of a Risk Prediction Model for Stress Urinary Incontinence in Pelvic Organ Prolapse：A simple screening toolSemantic proximity
Preoperative intrinsic capacity phenotypes forecast adverse physical resilience trajectories following surgery in older bladder cancer patients.Semantic proximity
Lifestyle and occupational risk assessment using machine learning methods and development a web-based nomogram for prediction of bladder cancer Short title: Risk assessment and nomogram to predict bladder cancerSemantic proximity
Identifying Distinct High Unmet-Need Phenotypes and Their Associated Bladder Cancer Patient Demographic, Clinical, Psychosocial, and Functional Characteristics: Results of Two Clustering Methods.Semantic proximity
Development of machine learning models for the prediction of complications after colorectal and small intestine surgery in psychiatric and non-psychiatric patient collectives (P-Study)Semantic proximity
Financial toxicity profiles and influencing factors among ovarian cancer Patients: a latent profile analysisSemantic proximity
Efficacy and safety of radical cystectomy with ileal conduit for muscle-invasive bladder cancer in the elderly: a multicentre retrospective studySemantic proximity
Simple Linear Cancer Risk Prediction Models with Novel Features Outperform Complex ApproachesSemantic proximity
Trajectory Analysis and Influencing Factors of Fear of Cancer Recurrence Discrepancies Between Colorectal Cancer patients and Their CaregiversSemantic proximity
An Integrated Random Forest– and LASSO-Derived Nomogram for Predicting Postoperative Nosocomial Infections in Colorectal Cancer PatientsSemantic proximity
Select a neighboring publication to make it the new centre.