AI Medical Compendium Topic

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

Decision Trees

Showing 201 to 210 of 527 articles

Clear Filters

Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia.

Environmental science and pollution research international
Reliable and accurate prediction model capturing the changes in solar radiation is essential in the power generation and renewable carbon-free energy industry. Malaysia has immense potential to develop such an industry due to its location in the equa...

Added value of deep learning-based liver parenchymal CT volumetry for predicting major arterial injury after blunt hepatic trauma: a decision tree analysis.

Abdominal radiology (New York)
PURPOSE: In patients presenting with blunt hepatic injury (BHI), the utility of CT for triage to hepatic angiography remains uncertain since simple binary assessment of contrast extravasation (CE) as being present or absent has only modest accuracy f...

Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...

Data mining for pesticide decontamination using heterogeneous photocatalytic processes.

Chemosphere
Pesticides are chemical compounds used to kill pests and weeds. Due to their nature, pesticides are potentially toxic to many organisms, including humans. Among the various methods used to decontaminate pesticides from the environment, the heterogene...

Imbalanced learning: Improving classification of diabetic neuropathy from magnetic resonance imaging.

PloS one
One of the fundamental challenges when dealing with medical imaging datasets is class imbalance. Class imbalance happens where an instance in the class of interest is relatively low, when compared to the rest of the data. This study aims to apply ove...

Classification of Biodegradable Substances Using Balanced Random Trees and Boosted C5.0 Decision Trees.

International journal of environmental research and public health
Substances that do not degrade over time have proven to be harmful to the environment and are dangerous to living organisms. Being able to predict the biodegradability of substances without costly experiments is useful. Recently, the quantitative str...

Identification of contributing genes of Huntington's disease by machine learning.

BMC medical genomics
BACKGROUND: Huntington's disease (HD) is an inherited disorder caused by the polyglutamine (poly-Q) mutations of the HTT gene results in neurodegeneration characterized by chorea, loss of coordination, cognitive decline. However, HD pathogenesis is s...

A random forest based biomarker discovery and power analysis framework for diagnostics research.

BMC medical genomics
BACKGROUND: Biomarker identification is one of the major and important goal of functional genomics and translational medicine studies. Large scale -omics data are increasingly being accumulated and can provide vital means for the identification of bi...

Analytics with artificial intelligence to advance the treatment of acute respiratory distress syndrome.

Journal of evidence-based medicine
Artificial intelligence (AI) has found its way into clinical studies in the era of big data. Acute respiratory distress syndrome (ARDS) or acute lung injury (ALI) is a clinical syndrome that encompasses a heterogeneous population. Management of such ...