AIMC Topic: Decision Trees

Clear Filters Showing 531 to 540 of 600 articles

[Constructing a predictive model for the death risk of patients with septic shock based on supervised machine learning algorithms].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To construct and validate the best predictive model for 28-day death risk in patients with septic shock based on different supervised machine learning algorithms.

Data-Driven Clinical Pharmacy Research: Utilizing Machine Learning and Medical Big Data.

Biological & pharmaceutical bulletin
To conduct clinical pharmacy research, we often face the limitations of conventional statistical methods and single-center observational study. To overcome these issues, we have conducted data-driven research using machine learning methods and medica...

A machine learning prediction model for cancer risk in patients with type 2 diabetes based on clinical tests.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The incidence of type 2 diabetes is rapidly increasing worldwide. Studies have shown that it is also associated with cancer-related morbidities. Early detection of cancer in patients with type 2 diabetes is crucial.

Deep learning based decision tree ensembles for incomplete medical datasets.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: In practice, the collected datasets for data analysis are usually incomplete as some data contain missing attribute values. Many related works focus on constructing specific models to produce estimations to replace the missing values, to ...

Decision Tree Versus Linear Support Vector Machine Classifier in the Screening of Medial Speech Sounds: A Quest for a Sound Rationale.

Studies in health technology and informatics
This paper describes the latest development in the classification stage of our Speech Sound Disorder (SSD) Screening algorithm and presents the results achieved by using two classifier models: the Classification and Regression Tree (CART)-based model...

The derivation of an International Classification of Diseases, Tenth Revision-based trauma-related mortality model using machine learning.

The journal of trauma and acute care surgery
BACKGROUND: Existing mortality prediction models have attempted to quantify injury burden following trauma-related admissions with the most notable being the Injury Severity Score (ISS). Although easy to calculate, it requires additional administrati...

Prediction of diagnosis and prognosis of COVID-19 disease by blood gas parameters using decision trees machine learning model: a retrospective observational study.

Medical gas research
The coronavirus disease 2019 (COVID-19) epidemic went down in history as a pandemic caused by corona-viruses that emerged in 2019 and spread rapidly around the world. The different symptoms of COVID-19 made it difficult to understand which variables ...

Identification of haploinsufficient genes from epigenomic data using deep forest.

Briefings in bioinformatics
Haploinsufficiency, wherein a single allele is not enough to maintain normal functions, can lead to many diseases including cancers and neurodevelopmental disorders. Recently, computational methods for identifying haploinsufficiency have been develop...

GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest.

Briefings in bioinformatics
Predicting disease-related long non-coding RNAs (lncRNAs) is beneficial to finding of new biomarkers for prevention, diagnosis and treatment of complex human diseases. In this paper, we proposed a machine learning techniques-based classification appr...