AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Decision Trees

Showing 411 to 420 of 528 articles

Clear Filters

PDP-CON: prediction of domain/linker residues in protein sequences using a consensus approach.

Journal of molecular modeling
The prediction of domain/linker residues in protein sequences is a crucial task in the functional classification of proteins, homology-based protein structure prediction, and high-throughput structural genomics. In this work, a novel consensus-based ...

A Prognosis Tool Based on Fuzzy Anthropometric and Questionnaire Data for Obstructive Sleep Apnea Severity.

Journal of medical systems
Obstructive sleep apnea (OSA) are linked to the augmented risk of morbidity and mortality. Although polysomnography is considered a well-established method for diagnosing OSA, it suffers the weakness of time consuming and labor intensive, and require...

Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier.

Journal of medical systems
In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in diagnosis of heart arrhythmia. Discrete wavelet transform (DWT) is used to decompose ECG signals into different successive frequency bands. A set of ...

Accurate Segmentation of CT Male Pelvic Organs via Regression-Based Deformable Models and Multi-Task Random Forests.

IEEE transactions on medical imaging
Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to l...

Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
BACKGROUND: The authors have previously demonstrated highly reliable automated classification of free-text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine lea...

3D Fast Automatic Segmentation of Kidney Based on Modified AAM and Random Forest.

IEEE transactions on medical imaging
In this paper, a fully automatic method is proposed to segment the kidney into multiple components: renal cortex, renal column, renal medulla and renal pelvis, in clinical 3D CT abdominal images. The proposed fast automatic segmentation method of kid...

GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran.

Environmental monitoring and assessment
Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learnin...

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

PloS one
Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biolog...

Can Robot-Assisted Unicompartmental Knee Arthroplasty Be Cost-Effective? A Markov Decision Analysis.

The Journal of arthroplasty
BACKGROUND: Unicompartmental knee arthroplasty (UKA) is a treatment option for single-compartment knee osteoarthritis. Robotic assistance may improve survival rates of UKA, but the cost-effectiveness of robot-assisted UKA is unknown. The purpose of t...

A Minimum Spanning Forest-Based Method for Noninvasive Cancer Detection With Hyperspectral Imaging.

IEEE transactions on bio-medical engineering
GOAL: The purpose of this paper is to develop a classification method that combines both spectral and spatial information for distinguishing cancer from healthy tissue on hyperspectral images in an animal model.