AIMC Topic: Decision Trees

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FS-GBDT: identification multicancer-risk module via a feature selection algorithm by integrating Fisher score and GBDT.

Briefings in bioinformatics
Cancer is a highly heterogeneous disease caused by dysregulation in different cell types and tissues. However, different cancers may share common mechanisms. It is critical to identify decisive genes involved in the development and progression of can...

Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.

Medicine
Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis treatment. Some studies have predicted mortality and development of sepsis using machine learning m...

treeheatr: an R package for interpretable decision tree visualizations.

Bioinformatics (Oxford, England)
SUMMARY: treeheatr is an R package for creating interpretable decision tree visualizations with the data represented as a heatmap at the tree's leaf nodes. The integrated presentation of the tree structure along with an overview of the data efficient...

Artificial intelligence in prediction of non-alcoholic fatty liver disease and fibrosis.

Journal of gastroenterology and hepatology
Artificial intelligence (AI) has become increasingly widespread in our daily lives, including healthcare applications. AI has brought many new insights into better ways we care for our patients with chronic liver disease, including non-alcoholic fatt...

An Optimized Decision Tree with Genetic Algorithm Rule-Based Approach to Reveal the Brain's Changes During Alzheimer's Disease Dementia.

Journal of Alzheimer's disease : JAD
BACKGROUND: It is desirable to achieve acceptable accuracy for computer aided diagnosis system (CADS) to disclose the dementia-related consequences on the brain. Therefore, assessing and measuring these impacts is fundamental in the diagnosis of deme...

Detection of Asymptomatic Carotid Artery Stenosis in High-Risk Individuals of Stroke Using a Machine-Learning Algorithm.

Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih
Objective Asymptomatic carotid stenosis (ACS) is closely associated to the incidence of severe cerebrovascular diseases. Early identifying the individuals with ACS and its associated risk factors could be beneficial for primary prevention of stroke. ...

An approach to predicting patient experience through machine learning and social network analysis.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Improving the patient experience has become an essential component of any healthcare system's performance metrics portfolio. In this study, we developed a machine learning model to predict a patient's response to the Hospital Consumer Asse...

A systematic literature review of automatic Alzheimer's disease detection from speech and language.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In recent years numerous studies have achieved promising results in Alzheimer's Disease (AD) detection using automatic language processing. We systematically review these articles to understand the effectiveness of this approach, identify ...