AIMC Topic: Proportional Hazards Models

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Machine-learning analysis of contrast-enhanced CT radiomics predicts recurrence of hepatocellular carcinoma after resection: A multi-institutional study.

EBioMedicine Nov 15, 2019
BACKGROUND: Current guidelines recommend surgical resection as the first-line option for patients with solitary hepatocellular carcinoma (HCC); unfortunately, postoperative recurrence rate remains high and there is no reliable prediction tool. We exp...
Machine Learning Algorithms Prognosis Retrospective Studies Tomography, X-Ray Computed Contrast Media Humans Workflow Neoplasm Recurrence, Local Hepatectomy Proportional Hazards Models Radiographic Image Enhancement Female Male Liver Neoplasms Carcinoma, Hepatocellular Image Processing, Computer-Assisted
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Development and verification of prediction models for preventing cardiovascular diseases.

PloS one Sep 19, 2019
OBJECTIVES: Cardiovascular disease (CVD) is one of the major causes of death worldwide. For improved accuracy of CVD prediction, risk classification was performed using national time-series health examination data. The data offers an opportunity to a...
Deep Learning Adult Blood Pressure Male Humans Cardiovascular Diseases Survival Analysis Algorithms Middle Aged Proportional Hazards Models Prognosis Risk Assessment Models, Cardiovascular Female Risk Factors
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CT Texture Analysis and Machine Learning Improve Post-ablation Prognostication in Patients with Adrenal Metastases: A Proof of Concept.

Cardiovascular and interventional radiology Sep 5, 2019
INTRODUCTION: To assess the performance of pre-ablation computed tomography texture features of adrenal metastases to predict post-treatment local progression and survival in patients who underwent ablation using machine learning as a prediction tool...
Humans Machine Learning Prognosis Retrospective Studies Pilot Projects ROC Curve Treatment Outcome Support Vector Machine Adrenal Gland Neoplasms Tomography, X-Ray Computed Female Male Middle Aged Disease Progression Survival Analysis Proportional Hazards Models Ablation Techniques
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A large cohort study identifying a novel prognosis prediction model for lung adenocarcinoma through machine learning strategies.

BMC cancer Sep 5, 2019
BACKGROUND: Predicting lung adenocarcinoma (LUAD) risk is crucial in determining further treatment strategies. Molecular biomarkers may improve risk stratification for LUAD.
Multivariate Analysis Kaplan-Meier Estimate Genes, Neoplasm Adenocarcinoma of Lung Male Middle Aged Disease Progression Transcriptome Lung Neoplasms Gene Expression Regulation, Neoplastic Follow-Up Studies Databases, Genetic Disease-Free Survival Proportional Hazards Models Prognosis Humans Female Machine Learning Aged Survival Rate Biomarkers, Tumor
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Deep Learning using Convolutional LSTM estimates Biological Age from Physical Activity.

Scientific reports Aug 6, 2019
Human age estimation is an important and difficult challenge. Different biomarkers and numerous approaches have been studied for biological age estimation, each with its advantages and limitations. In this work, we investigate whether physical activi...
Accelerometry Anthropometry Middle Aged Datasets as Topic Exercise Proportional Hazards Models Deep Learning Locomotion Wearable Electronic Devices Kaplan-Meier Estimate Aged Nutrition Surveys Mobile Applications Young Adult Health Status Humans Adult Monitoring, Physiologic Female Male Models, Biological Reproducibility of Results Aging Telemedicine
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A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk.

Breast cancer research : BCR Jul 29, 2019
BACKGROUND: Breast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected breast cancers. The overall risk for DCIS patients treated with breast-conserving surgery stems almost exclusively from local recurrence. Although a mas...
Immunohistochemistry Aged, 80 and over Proportional Hazards Models Adult Breast Neoplasms Humans Mastectomy Biomarkers, Tumor Machine Learning Risk Assessment Middle Aged Prognosis Carcinoma, Intraductal, Noninfiltrating Neoplasm Staging Female Neoplasm Grading Neoplasm Recurrence, Local Aged
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A deep survival analysis method based on ranking.

Artificial intelligence in medicine Jun 6, 2019
Survival analyses of populations and the establishment of prognoses for individual patients are important activities in the practice of medicine. Standard survival models, such as the Cox proportional hazards model, require extensive feature engineer...
Humans Neural Networks, Computer Prognosis Breast Neoplasms Deep Learning Neoplasm Recurrence, Local Myocardial Infarction Survival Analysis Proportional Hazards Models Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms
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Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants.

PloS one May 15, 2019
BACKGROUND: Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-op...
Risk Assessment Population Surveillance Biological Specimen Banks United Kingdom Proportional Hazards Models Female Humans Reproducibility of Results Machine Learning Risk Factors Algorithms Male Prospective Studies Cardiovascular Diseases Prognosis
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Deep learning-based survival prediction of oral cancer patients.

Scientific reports May 6, 2019
The Cox proportional hazards model commonly used to evaluate prognostic variables in survival of cancer patients may be too simplistic to properly predict a cancer patient's outcome since it assumes that the outcome is a linear combination of covaria...
Mouth Neoplasms Survival Analysis Proportional Hazards Models Recurrence Carcinoma, Squamous Cell Humans Aged Prognosis Male Retrospective Studies Middle Aged Female Deep Learning
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Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer.

Cellular oncology (Dordrecht, Netherlands) Apr 15, 2019
PURPOSE: The prognostic value of mitotic count for invasive breast cancer is firmly established. As yet, however, limited studies have been aimed at assessing mitotic counts as a prognostic factor for triple negative breast cancers (TNBC). Here, we a...
Mitosis Deep Learning Triple Negative Breast Neoplasms Disease-Free Survival Proportional Hazards Models Multivariate Analysis Humans Algorithms Prognosis Female Middle Aged
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