AIMC Topic: Survival Rate

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Machine learning in predicting gastric cancer survival Presenting a novel decision support system model.

Annali italiani di chirurgia
BACKGROUND: Gastric cancer is the 4th most frequent cause of cancer-related deaths, with a 5-year survival rate of less than 40%. In recent years, many artificial intelligence applications have been used in the field of gastric cancer through their e...

An app to classify a 5-year survival in patients with breast cancer using the convolutional neural networks (CNN) in Microsoft Excel: Development and usability study.

Medicine
BACKGROUND: Breast cancer (BC) is the most common malignant cancer in women. A predictive model is required to predict the 5-year survival in patients with BC (5YSPBC) and improve the treatment quality by increasing their survival rate. However, no r...

Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients.

Open heart
OBJECTIVES: Identifying high-risk patients is crucial for effective cardiovascular disease (CVD) prevention. It is not known whether electronic health record (EHR)-based machine-learning (ML) models can improve CVD risk stratification compared with a...

Machine learning-based integrative analysis of methylome and transcriptome identifies novel prognostic DNA methylation signature in uveal melanoma.

Briefings in bioinformatics
Uveal melanoma (UVM) is the most common primary intraocular human malignancy with a high mortality rate. Aberrant DNA methylation has rapidly emerged as a diagnostic and prognostic signature in many cancers. However, such DNA methylation signature av...

Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma.

The Journal of clinical investigation
BACKGROUNDPatients with p16+ oropharyngeal squamous cell carcinoma (OPSCC) are potentially cured with definitive treatment. However, there are currently no reliable biomarkers of treatment failure for p16+ OPSCC. Pathologist-based visual assessment o...

Identifying key predictors of mortality in young patients on chronic haemodialysis-a machine learning approach.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: The mortality risk remains significant in paediatric and adult patients on chronic haemodialysis (HD) treatment. We aimed to identify factors associated with mortality in patients who started HD as children and continued HD as adults.

Predictors of Survival among Male and Female Patients with Malignant Pleural Mesothelioma: A Random Survival Forest Analysis of Data from the 2000-2017 Surveillance, Epidemiology, and End Results Program.

Journal of registry management
BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive malignancy with a dismal prognosis. We aimed to identify predictors of survival among male and female MPM patients in the United States.

Prognosticating Outcome in Pancreatic Head Cancer With the use of a Machine Learning Algorithm.

Technology in cancer research & treatment
The purpose of this project is to identify prognostic features in resectable pancreatic head adenocarcinoma and use these features to develop a machine learning algorithm that prognosticates survival for patients pursuing pancreaticoduodenectomy. A...

Prediction of survival rate and effect of drugs on cancer patients with somatic mutations of genes: An AI-based approach.

Chemical biology & drug design
The causal role of somatic mutation and its interrelationship with gene expression profile during tumor development has already been observed, which plays a major role to decide the cancer grades and overall survival. Accurate and robust prediction o...

Prediction of all-cause mortality in haemodialysis patients using a Bayesian network.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: All-cause mortality in haemodialysis (HD) is high, reaching 15.6% in the first year according to the European Renal Association.