AIMC Topic: Proportional Hazards Models
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Random survival forests for dynamic predictions of a time-to-event outcome using a longitudinal biomarker.
BMC medical research methodology
Oct 17, 2021
BACKGROUND: Risk prediction models for time-to-event outcomes play a vital role in personalized decision-making. A patient's biomarker values, such as medical lab results, are often measured over time but traditional prediction models ignore their lo...
Sentiment Analysis Based on the Nursing Notes on In-Hospital 28-Day Mortality of Sepsis Patients Utilizing the MIMIC-III Database.
Computational and mathematical methods in medicine
Oct 13, 2021
In medical visualization, nursing notes contain rich information about a patient's pathological condition. However, they are not widely used in the prediction of clinical outcomes. With advances in the processing of natural language, information begi...
Continuous and discrete-time survival prediction with neural networks.
Lifetime data analysis
Oct 7, 2021
Due to rapid developments in machine learning, and in particular neural networks, a number of new methods for time-to-event predictions have been developed in the last few years. As neural networks are parametric models, it is more straightforward to...
Improved breast cancer histological grading using deep learning.
Annals of oncology : official journal of the European Society for Medical Oncology
Sep 29, 2021
BACKGROUND: The Nottingham histological grade (NHG) is a well-established prognostic factor for breast cancer that is broadly used in clinical decision making. However, ∼50% of patients are classified as grade 2, an intermediate risk group with low c...
A comparative study of forest methods for time-to-event data: variable selection and predictive performance.
BMC medical research methodology
Sep 25, 2021
BACKGROUND: As a hot method in machine learning field, the forests approach is an attractive alternative approach to Cox model. Random survival forests (RSF) methodology is the most popular survival forests method, whereas its drawbacks exist such as...
Machine learning risk prediction model for acute coronary syndrome and death from use of non-steroidal anti-inflammatory drugs in administrative data.
Scientific reports
Sep 15, 2021
Our aim was to investigate the usefulness of machine learning approaches on linked administrative health data at the population level in predicting older patients' one-year risk of acute coronary syndrome and death following the use of non-steroidal ...
The role of deep learning-based survival model in improving survival prediction of patients with glioblastoma.
Cancer medicine
Aug 28, 2021
This retrospective study has been conducted to validate the performance of deep learning-based survival models in glioblastoma (GBM) patients alongside the Cox proportional hazards model (CoxPH) and the random survival forest (RSF). Furthermore, the ...
Radiotherapy
Isocitrate Dehydrogenase
Karnofsky Performance Status
Tumor Suppressor Proteins
Proportional Hazards Models
Chemoradiotherapy
Age Factors
Predictive Value of Tests
Glioblastoma
Bayes Theorem
Sex Factors
Survival Analysis
DNA Modification Methylases
DNA Repair Enzymes
Brain Neoplasms
Male
Humans
Middle Aged
Retrospective Studies
Deep Learning
Female
Aged
Adult
The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model.
Frontiers in public health
Jul 5, 2021
An adequate imputation of missing data would significantly preserve the statistical power and avoid erroneous conclusions. In the era of big data, machine learning is a great tool to infer the missing values. The root means square error (RMSE) and th...
Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID).
Scientific reports
Jun 17, 2021
In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortality can significantly improve triage, bed allocation, timely management, and possibly, outcome. The study objective is to develop and validate individu...
Clinical use of machine learning-based pathomics signature for diagnosis and survival prediction of bladder cancer.
Cancer science
May 5, 2021
Traditional histopathology performed by pathologists by the naked eye is insufficient for accurate and efficient diagnosis of bladder cancer (BCa). We collected 643 H&E-stained BCa images from Shanghai General Hospital and The Cancer Genome Atlas (TC...
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