AIMC Topic: Kaplan-Meier Estimate

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Integrated machine learning developed a prognosis-related gene signature to predict prognosis in oesophageal squamous cell carcinoma.

Journal of cellular and molecular medicine Nov 1, 2024
The mortality rate of oesophageal squamous cell carcinoma (ESCC) remains high, and conventional TNM systems cannot accurately predict its prognosis, thus necessitating a predictive model. In this study, a 17-gene prognosis-related gene signature (PRS...
Humans Machine Learning Algorithms Prognosis Female Transcriptome ROC Curve Gene Expression Regulation, Neoplastic Esophageal Neoplasms Kaplan-Meier Estimate Esophageal Squamous Cell Carcinoma Aged Biomarkers, Tumor Male Middle Aged Gene Expression Profiling
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Identification of novel M2 macrophage-related molecule ATP6V1E1 and its biological role in hepatocellular carcinoma based on machine learning algorithms.

Journal of cellular and molecular medicine Sep 1, 2024
Hepatocellular carcinoma (HCC) remains the most prevalent form of primary liver cancer, characterized by late detection and suboptimal response to current therapies. The tumour microenvironment, especially the role of M2 macrophages, is pivotal in th...
Vacuolar Proton-Translocating ATPases Liver Neoplasms Carcinoma, Hepatocellular Gene Expression Regulation, Neoplastic Cell Proliferation Kaplan-Meier Estimate Humans Machine Learning Macrophages Prognosis Female Tumor Microenvironment Biomarkers, Tumor Male Middle Aged Cell Line, Tumor
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[Prediction of risk of in-hospital death in patients with chronic heart failure complicated by lung infections using interpretable machine learning].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Jun 20, 2024
OBJECTIVE: To predict the risk of in-hospital death in patients with chronic heart failure (CHF) complicated by lung infections using interpretable machine learning.
Humans Machine Learning Algorithms Pneumonia, Bacterial Hospital Mortality Female Chronic Disease Risk Factors Pneumonia Aged Heart Failure Male Kaplan-Meier Estimate Middle Aged
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Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis.

World journal of gastroenterology Apr 21, 2024
BACKGROUND: The prognosis for hepatocellular carcinoma (HCC) in the presence of cirrhosis is unfavourable, primarily attributable to the high incidence of recurrence.
Adult Radiomics Male Middle Aged Risk Assessment ROC Curve Retrospective Studies Tomography, X-Ray Computed Female Risk Factors Aged Neoplasm Recurrence, Local Hepatectomy Kaplan-Meier Estimate Liver Neoplasms Carcinoma, Hepatocellular Liver Cirrhosis Liver Predictive Value of Tests Humans Machine Learning Prognosis
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Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma.

Technology in cancer research & treatment Jan 1, 2024
Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and ...
Computational Biology Gene Expression Regulation, Neoplastic Mutation Kidney Neoplasms Proportional Hazards Models Kaplan-Meier Estimate Carcinoma, Renal Cell Gene Ontology Female Biomarkers, Tumor Humans Male Machine Learning Middle Aged Algorithms Gene Expression Profiling Prognosis
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Statistical and Machine Learning Methods for Discovering Prognostic Biomarkers for Survival Outcomes.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2023
Discovering molecular biomarkers for predicting patient survival outcomes is an essential step toward improving prognosis and therapeutic decision-making in the treatment of severe diseases such as cancer. Due to the high-dimensionality nature of omi...
Kaplan-Meier Estimate Prognosis Female Biomarkers, Tumor Male Deep Learning Lung Neoplasms Head and Neck Neoplasms Programming Languages Survival Analysis Datasets as Topic Proportional Hazards Models Humans Neural Networks, Computer Machine Learning Biomarkers
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Bioinformatics and machine learning methodologies to identify the effects of central nervous system disorders on glioblastoma progression.

Briefings in bioinformatics Sep 2, 2021
Glioblastoma (GBM) is a common malignant brain tumor which often presents as a comorbidity with central nervous system (CNS) disorders. Both CNS disorders and GBM cells release glutamate and show an abnormality, but differ in cellular behavior. So, t...
Humans Machine Learning Brain Neoplasms Gene Expression Profiling Gene Regulatory Networks Computational Biology Gene Expression Regulation, Neoplastic Signal Transduction Neoplasm Proteins Glioblastoma Datasets as Topic Atlases as Topic Central Nervous System Glutamic Acid Proportional Hazards Models Kaplan-Meier Estimate Molecular Sequence Annotation Gene Ontology
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Automated model versus treating physician for predicting survival time of patients with metastatic cancer.

Journal of the American Medical Informatics Association : JAMIA Jun 12, 2021
OBJECTIVE: Being able to predict a patient's life expectancy can help doctors and patients prioritize treatments and supportive care. For predicting life expectancy, physicians have been shown to outperform traditional models that use only a few pred...
Area Under Curve Neoplasm Metastasis Kaplan-Meier Estimate Life Expectancy Radiation Oncologists Aged Humans Male Machine Learning Middle Aged Prognosis Neoplasms Electronic Health Records ROC Curve Female
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Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs.

The Lancet. Digital health May 1, 2021
BACKGROUND: Coronary artery calcium (CAC) score is a clinically validated marker of cardiovascular disease risk. We developed and validated a novel cardiovascular risk stratification system based on deep-learning-predicted CAC from retinal photograph...
Deep Learning Humans ROC Curve Algorithms Predictive Value of Tests Vascular Calcification Coronary Artery Disease Adult Republic of Korea Area Under Curve Male Female Singapore Retina Cardiovascular Diseases Aged Middle Aged United Kingdom Proportional Hazards Models Risk Assessment Kaplan-Meier Estimate
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Independent Validation of a Comprehensive Machine Learning Approach Predicting Survival After Radiotherapy for Bone Metastases.

Anticancer research Mar 1, 2021
BACKGROUND/AIM: The aim of this study was to analyze the survival predictions obtained from a web platform allowing for computation of the so-called Bone Metastases Ensemble Trees for Survival (BMETS). This prediction model is based on a machine lear...
Lung Neoplasms Aged, 80 and over Humans Bone Neoplasms Adult Kaplan-Meier Estimate Breast Neoplasms Machine Learning Radiation Oncology Male Prognosis Prostatic Neoplasms Middle Aged Retrospective Studies Palliative Care Aged
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