AI Medical Compendium Topic

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

Decision Trees

Showing 121 to 130 of 525 articles

Clear Filters

Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.

European radiology
OBJECTIVE: To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (PCa) in a large, single-institu...

A machine learning algorithm-based predictive model for pressure injury risk in emergency patients: A prospective cohort study.

International emergency nursing
OBJECTIVES: To construct pressure injury risk prediction models for emergency patients based on different machine learning algorithms, to optimize the best model, and to provide a suitable assessment tool for preventing the occurrence of pressure inj...

A precise blood transfusion evaluation model for aortic surgery: a single-center retrospective study.

Journal of clinical monitoring and computing
Cardiac aortic surgery is an extremely complicated procedure that often requires large volume blood transfusions during the operation. Currently, it is not possible to accurately estimate the intraoperative blood transfusion volume before surgery. Th...

Toxicity prediction of nanoparticles using machine learning approaches.

Toxicology
Nanoparticle toxicity analysis is critical for evaluating the safety of nanomaterials due to their potential harm to the biological system. However, traditional experimental methods for evaluating nanoparticle toxicity are expensive and time-consumin...

Identification and Classification of Human Body Exercises on Smart Textile Bands by Combining Decision Tree and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
In recent years, human activity recognition (HAR) has gained significant interest from researchers in the sports and fitness industries. In this study, the authors have proposed a cascaded method including two classifying stages to classify fitness e...

Robust Virtual Sensing of the Vehicle Sideslip Angle through the Cross-Combination of Multiple Filters Using a Decision Tree Algorithm.

Sensors (Basel, Switzerland)
This paper presents a state-of-the-art estimation technique by cross-combining a number n of filters for high-precision, reliable and robust vehicle sideslip angle state estimation, over a full range of vehicle operations irrespective of the driving ...

Automated grading of anatomical objective structured practical examinations using decision trees: An artificial intelligence approach.

Anatomical sciences education
An Objective Structured Practical Examination (OSPE) is an effective and robust, but resource-intensive, means of evaluating anatomical knowledge. Since most OSPEs employ short answer or fill-in-the-blank style questions, the format requires many peo...

Classification and Recognition of Building Appearance Based on Optimized Gradient-Boosted Decision Tree Algorithm.

Sensors (Basel, Switzerland)
There are high concentrations of urban spaces and increasingly complex land use types. Providing an efficient and scientific identification of building types has become a major challenge in urban architectural planning. This study used an optimized g...

Machine Learning and Electroencephalogram Signal based Diagnosis of Dipression.

Neuroscience letters
Depression is a psychological condition which hampers day to day activity (Thinking, Feeling or Action). The early detection of this illness will help to save many lives because it is now recognized as a global problem which could even lead to suicid...

Development of prediction software to describe total mesophilic bacteria in spinach using a machine learning-based regression approach.

Food science and technology international = Ciencia y tecnologia de los alimentos internacional
The purpose of this study was to create a tool for predicting the growth of total mesophilic bacteria in spinach using machine learning-based regression models such as support vector regression, decision tree regression, and Gaussian process regressi...