AIMC Topic: Survival Analysis
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Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.
Cancer science
Sep 2, 2024
This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with pr...
Multi-metric comparison of machine learning imputation methods with application to breast cancer survival.
BMC medical research methodology
Aug 30, 2024
Handling missing data in clinical prognostic studies is an essential yet challenging task. This study aimed to provide a comprehensive assessment of the effectiveness and reliability of different machine learning (ML) imputation methods across variou...
Survival analysis for lung cancer patients: A comparison of Cox regression and machine learning models.
International journal of medical informatics
Aug 26, 2024
INTRODUCTION: Survival analysis based on cancer registry data is of paramount importance for monitoring the effectiveness of health care. As new methods arise, the compendium of statistical tools applicable to cancer registry data grows. In recent ye...
Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy.
NPJ systems biology and applications
Aug 14, 2024
We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based ...
Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non-small-cell lung cancer.
Journal of translational medicine
Aug 5, 2024
Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant challenge for the scientific and clinical community despite decades of advanced analytics. Addressing this challenge not only helps inform the critical...
Towards key genes identification for breast cancer survival risk with neural network models.
Computational biology and chemistry
Aug 2, 2024
Breast cancer, one common malignant tumor all over the world, has a considerably high rate of recurrence, which endangers the health and life of patients. While more and more data have been available, how to leverage the gene expression data to predi...
Machine learning identifies prognostic subtypes of the tumor microenvironment of NSCLC.
Scientific reports
Jul 1, 2024
The tumor microenvironment (TME) plays a fundamental role in tumorigenesis, tumor progression, and anti-cancer immunity potential of emerging cancer therapeutics. Understanding inter-patient TME heterogeneity, however, remains a challenge to efficien...
A deep learning approach for overall survival prediction in lung cancer with missing values.
Computer methods and programs in biomedicine
Jun 28, 2024
BACKGROUND AND OBJECTIVE: In the field of lung cancer research, particularly in the analysis of overall survival (OS), artificial intelligence (AI) serves crucial roles with specific aims. Given the prevalent issue of missing data in the medical doma...
Prediction of prognosis in patients with systemic sclerosis based on a machine-learning model.
Clinical rheumatology
Jun 28, 2024
OBJECTIVE: The clinical manifestations of systemic sclerosis (SSc) are highly variable, resulting in varied outcomes and complications. Diverse fibrosis of the skin and internal organs, vasculopathy, and dysregulated immune system lead to poor and va...
Dual-stream multi-dependency graph neural network enables precise cancer survival analysis.
Medical image analysis
Jun 26, 2024
Histopathology image-based survival prediction aims to provide a precise assessment of cancer prognosis and can inform personalized treatment decision-making in order to improve patient outcomes. However, existing methods cannot automatically model t...
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