AIMC Topic: Nomograms
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Comparative Analysis of Nomogram and Machine Learning Models for Predicting Axillary Lymph Node Metastasis in Early-Stage Breast Cancer: A Study on Clinically and Ultrasound-Negative Axillary Cases Across Two Centers.
Ultrasound in medicine & biology
Dec 3, 2024
OBJECTIVE: Early and accurate prediction of axillary lymph node metastasis (ALNM) is crucial in determining appropriate treatment strategies for patients with early-stage breast cancer. The aim of this study was to evaluate the efficacy of radiomic f...
The diagnostic value investigation of programmed cell death genes in heart failure.
BMC cardiovascular disorders
Nov 22, 2024
BACKGROUND: We aimed to identify the potential diagnostic markers and associated molecular mechanisms based on programmed cell death (PCD)-related genes in patients with heart failure (HF).
Transcriptome
Apoptosis Regulatory Proteins
Case-Control Studies
Genetic Markers
Protein Interaction Maps
Heart Failure
Gene Regulatory Networks
Plasminogen Activator Inhibitor 1
Humans
Gene Expression Regulation
Machine Learning
Nomograms
Reproducibility of Results
Databases, Genetic
Gene Expression Profiling
Apoptosis
Predictive Value of Tests
Development of a simplified model and nomogram for the prediction of pulmonary hemorrhage in respiratory distress syndrome in extremely preterm infants.
BMC pediatrics
Nov 21, 2024
BACKGROUND: Pulmonary hemorrhage (PH) in respiratory distress syndrome (RDS) in extremely preterm infants exhibits a high mortality rate and poor long-term outcomes. The aim of the present study was to develop a machine learning (ML) predictive model...
Machine learning model-based preterm birth prediction and clinical nomogram: A big retrospective cohort study.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Nov 18, 2024
OBJECTIVE: This study sought to develop a multifactorial predictive model for preterm birth risk, with the goal of providing clinical practitioners with early prevention.
Explainable machine learning versus known nomogram for predicting non-sentinel lymph node metastases in breast cancer patients: A comparative study.
Computers in biology and medicine
Nov 16, 2024
INTRODUCTION: Axillary lymph node dissection (ALND) is the standard of care for breast cancer patients with positive sentinel lymph nodes (SLN), which are the first lymph nodes that drain the breast. However, many patients with positive SLNs may not ...
Machine learning algorithms using the inflammatory prognostic index for contrast-induced nephropathy in NSTEMI patients.
Biomarkers in medicine
Nov 13, 2024
Inflammatory prognostic index (IPI), has been shown to be related with poor outcomes in cancer patients. We aimed to investigate the predictive role of IPI for contrast-induced nephropathy (CIN) development in non-ST segment elevation myocardial inf...
Predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma: nomograms based on deep learning analysis of gadoxetic acid-enhanced MRI.
European radiology
Nov 12, 2024
OBJECTIVES: This study aimed to develop nomograms for predicting post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC), using deep learning analysis of Gadoxetic acid-enhanced hepatobiliary (HBP) MRI.
Development and Validation of a Machine Learning-Based Nomogram for Prediction of Unplanned Reoperation Postspinal Surgery Within 30 Days.
World neurosurgery
Nov 11, 2024
BACKGROUND: Unplanned reoperation postspinal surgery (URPS) leads to prolonged hospital stays, higher costs, decreased patient satisfaction, and adversely affects postoperative rehabilitation. This study aimed to develop and validate prediction model...
Machine Learning-enhanced Signature of Metastasis-related T Cell Marker Genes for Predicting Overall Survival in Malignant Melanoma.
Journal of immunotherapy (Hagerstown, Md. : 1997)
Nov 7, 2024
In this study, we aimed to investigate disparities in the tumor immune microenvironment (TME) between primary and metastatic malignant melanoma (MM) using single-cell RNA sequencing (scRNA- seq ) and to identify metastasis-related T cell marker genes...
Construction of a Wilms tumor risk model based on machine learning and identification of cuproptosis-related clusters.
BMC medical informatics and decision making
Nov 4, 2024
BACKGROUND: Cuproptosis, a recently identified type of programmed cell death triggered by copper, has mechanisms in Wilms tumor (WT) that are not yet fully understood. This research focuses on examining the link between WT and Cuproptosis-related gen...
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