AI Medical Compendium Topic:
Decision Trees

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Obstructive sleep apnea syndrome detection based on ballistocardiogram via machine learning approach.

Mathematical biosciences and engineering : MBE
Obstructive sleep apnea (OSA) is a common sleep-related respiratory disease that affects people's health, especially in the elderly. In the traditional PSG-based OSA detection, people's sleep may be disturbed, meanwhile the electrode slices are easil...

A novel machine learning-derived decision tree including uPA/PAI-1 for breast cancer care.

Clinical chemistry and laboratory medicine
Background uPA and PAI-1 are breast cancer biomarkers that evaluate the benefit of chemotherapy (CT) for HER2-negative, estrogen receptor-positive, low or intermediate grade patients. Our objectives were to observe clinical routine use of uPA/PAI-1 a...

A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic.

JCO clinical cancer informatics
PURPOSE: Dynamic network models predict clinical prognosis and inform therapeutic intervention by elucidating disease-driven aberrations at the systems level. However, the personalization of model predictions requires the profiling of multiple model ...

Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA.

Journal of the American Heart Association
Background We developed a new left ventricular hypertrophy ( LVH ) criterion using a machine-learning technique called Bayesian Additive Regression Trees ( BART ). Methods and Results This analysis included 4714 participants from MESA (Multi-Ethnic S...

Decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) models for sediment transport in sewer pipes.

Water science and technology : a journal of the International Association on Water Pollution Research
Sediment deposition in sewers and urban drainage systems has great effect on the hydraulic capacity of the channel. In this respect, the self-cleansing concept has been widely used for sewers and urban drainage systems design. This study investigates...

Machine Learning and Deep Learning Approaches in Breast Cancer Survival Prediction Using Clinical Data.

Folia biologica
Breast cancer survival prediction can have an extreme effect on selection of best treatment protocols. Many approaches such as statistical or machine learning models have been employed to predict the survival prospects of patients, but newer algorith...

Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies.

Current medical imaging reviews
BACKGROUND: Brain tumor is the leading cause of death worldwide. It is obvious that the chances of survival can be increased if the tumor is identified and properly classified at an initial stage. MRI (Magnetic Resonance Imaging) is one source of bra...

A Hybrid Approach for Sub-Acute Ischemic Stroke Lesion Segmentation Using Random Decision Forest and Gravitational Search Algorithm.

Current medical imaging reviews
BACKGROUND: The sub-acute ischemic stroke is the most basic illnesses reason for death on the planet. We evaluate the impact of segmentation technique during the time of breaking down the capacities of the cerebrum.

Volumetric Histogram-Based Alzheimer's Disease Detection Using Support Vector Machine.

Journal of Alzheimer's disease : JAD
In this research work, machine learning techniques are used to classify magnetic resonance imaging brain scans of people with Alzheimer's disease. This work deals with binary classification between Alzheimer's disease and cognitively normal. Supervis...

Dynamic Features Impact on the Quality of Chronic Heart Failure Predictive Modelling.

Studies in health technology and informatics
We study the way dynamics affects modelling in chronic heart failure (CHF) tasks. By dynamics we understand the patient history and the appearance of new events, states and variables changing in time. The goal is to understand what impact past data h...