AIMC Topic: Proportional Hazards Models
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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...
Kaplan-Meier Estimate
Female
Receptors, Interleukin-7
Aged
Interleukin-7 Receptor alpha Subunit
Adult
Radiomics
Support Vector Machine
Brain Neoplasms
Male
Humans
Magnetic Resonance Imaging
Middle Aged
Machine Learning
ROC Curve
Algorithms
Glioma
Prognosis
Neoplasm Grading
Proportional Hazards Models
Multivariate Analysis
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...
Development and evaluation of a multivariable prediction model for overall survival in advanced stage pulmonary carcinoid using machine learning.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Feb 25, 2025
BACKGROUND: Evidence is limited on whether patients with advanced pulmonary carcinoid (APC) benefit from comprehensive pulmonary resection (CPR), chemotherapy, or radiotherapy. Existing prognostic models for APC are limited and do not guide treatment...
Development of a Machine Learning-Powered Optimized Lung Allocation System for Maximum Benefits in Lung Transplantation: A Korean National Data.
Journal of Korean medical science
Feb 24, 2025
BACKGROUND: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize...
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