AIMC Topic: Proportional Hazards Models
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Data-driven survival modeling for breast cancer prognostics: A comparative study with machine learning and traditional survival modeling methods.
PloS one
Apr 22, 2025
Background This investigation delves into the potential application of data-driven survival modeling approaches for prognostic assessments of breast cancer survival. The primary objective is to evaluate and compare the ability of machine learning (ML...
Machine Learning-Enhanced Cerebrospinal Fluid N-Glycome for the Diagnosis and Prognosis of Primary Central Nervous System Lymphoma.
Journal of proteome research
Apr 21, 2025
The diagnosis and prognosis of Primary Central Nervous System Lymphoma (PCNSL) present significant challenges. In this study, the potential use of machine learning algorithms in diagnosing and predicting the prognosis for PCNSL based on cerebrospinal...
Investigating long-term risk of aortic aneurysm and dissection from fluoroquinolones and the key contributing factors using machine learning methods.
Scientific reports
Apr 16, 2025
The connection between fluoroquinolones and severe heart conditions, such as aortic aneurysm (AA) and aortic dissection (AD), has been acknowledged, but the full extent of long-term risks remains uncertain. Addressing this knowledge deficit, a retros...
Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice.
Journal of translational medicine
Mar 31, 2025
BACKGROUND: High-grade gliomas are among the most aggressive and deadly brain tumors, highlighting the critical need for improved prognostic markers and predictive models. Recent studies have identified the expression of IL7R as a significant risk fa...
Receptors, Interleukin-7
Interleukin-7 Receptor alpha Subunit
Neoplasm Grading
Proportional Hazards Models
Multivariate Analysis
Humans
Kaplan-Meier Estimate
ROC Curve
Machine Learning
Glioma
Support Vector Machine
Magnetic Resonance Imaging
Algorithms
Adult
Prognosis
Radiomics
Female
Brain Neoplasms
Aged
Male
Middle Aged
Enhancing prediction and stratifying risk: machine learning and bayesian-learning models for catheter-related thrombosis in chemotherapy patients.
BMC cancer
Mar 27, 2025
BACKGROUND: Catheter-related thrombosis (CRT) is a serious complication in cancer patients undergoing chemotherapy, yet existing risk prediction models demonstrate limited accuracy. This study aimed to evaluate the clinical utility of machine learnin...
A machine learning-based model for predicting survival in patients with Rectosigmoid Cancer.
PloS one
Mar 25, 2025
BACKGROUND: The unique anatomical characteristics and blood supply of the rectosigmoid junction confer particular significance to its physiological functions and clinical surgeries. However, research on the prognosis of rectosigmoid junction cancer (...
Using machine learning for predicting cancer-specific mortality in bladder cancer patients undergoing radical cystectomy: a SEER-based study.
BMC cancer
Mar 21, 2025
BACKGROUND: Accurately assessing the prognosis of bladder cancer patients after radical cystectomy has important clinical and research implications. Current models, based on traditional statistical approaches and complex variables, have limited perfo...
Development of PDAC diagnosis and prognosis evaluation models based on machine learning.
BMC cancer
Mar 20, 2025
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is difficult to detect early and highly aggressive, often leading to poor patient prognosis. Existing serum biomarkers like CA19-9 are limited in early diagnosis, failing to meet clinical needs. Mac...
Life's Crucial 9 and NAFLD from association to SHAP-interpreted machine learning predictions.
Scientific reports
Mar 18, 2025
Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. Cardiovascular disease (CVD) and NAFLD share multiple common risk factors. Life's Crucial 9 (LC9), a novel indicator for comprehensive assessment of card...
Factor enhanced DeepSurv: A deep learning approach for predicting survival probabilities in cirrhosis data.
Computers in biology and medicine
Mar 3, 2025
BACKGROUND: Over the years, various models, including both traditional and machine learning models, have been employed to predict survival probabilities for diverse survival datasets. The objective is to obtain models that provide more accurate estim...
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