AIMC Topic: Decision Trees

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Machine learning estimation and optimization for evaluation of pharmaceutical solubility in supercritical carbon dioxide for improvement of drug efficacy.

Scientific reports
This study focuses on predicting the solubility of paracetamol and density of solvent using temperature (T) and pressure (P) as inputs. The process for production of the drug is supercritical technique in which the focus was on theoretical investigat...

Decision tree-based machine learning methods for identifying colorectal cancer-associated microRNA signatures and their regulatory networks.

Scientific reports
This study aimed to identify candidate diagnostic miRNAs from the serum of colorectal cancer (CRC) patients using Boruta, a wrapper-based feature selection technique, in combination with decision tree-based machine learning methods. We analyzed three...

Estimation of sexual dimorphism of adult human mandibles of South Indian origin using non-metric parameters and machine learning classification algorithms.

Scientific reports
The mandible is one of the most reliable in sex determination in forensic anthropology. The shape of the mandible provides valuable information regarding the male and female distinctions. Machine learning algorithms are widely used for various applic...

Application of machine learning models for predicting depression among older adults with non-communicable diseases in India.

Scientific reports
Depression among older adults is a critical public health issue, particularly when coexisting with non-communicable diseases (NCDs). In India, where population ageing and NCDs burden are rising rapidly, scalable data-driven approaches are needed to i...

Introduction of sub-band augmentation with machine learning to develop an insomnia classification model using single-channel EEG signals.

Physiological measurement
. Biological signals can be used to record sleep activities and can be used to identify sleep disorders. Insomnia is a sleep disorder that can be detected using supervised learning models developed using biological signal analysis. The baseline insom...

Adaptive TreeHive: Ensemble of trees for enhancing imbalanced intrusion classification.

PloS one
Imbalanced intrusion classification is a complex and challenging task as there are few number of instances/intrusions generally considered as minority instances/intrusions in the imbalanced intrusion datasets. Data sampling methods such as over-sampl...

Integrating multiple feature assessment methods to identify key predictors of repeat suicide attempts in Taiwan.

BMC psychiatry
BACKGROUND: The high rate of repeat attempts among individuals who have previously attempted suicide presents a critical challenge in public health and suicide prevention. While early and targeted intervention is crucial for this high-risk group, eff...

Error recognition of english translation text based on neural network and fuzzy decision tree.

PloS one
In response to the low accuracy and recall of current English translation text error recognition methods, this paper proposes a research on English translation text error recognition based on an improved decision tree algorithm. Firstly, use mutual i...

Optimized machine learning based comparative analysis of predictive models for classification of kidney tumors.

Scientific reports
The kidney is an important organ that helps clean the blood by removing waste, extra fluids, and harmful substances. It also keeps the balance of minerals in the body and helps control blood pressure. But if the kidney gets sick, like from a tumor, i...

The potential of decision tree application in threshold analysis of hazardous volatile organic compound release from biochar: Implications for environmental risk assessment.

The Science of the total environment
The release of hazardous volatile organic compounds (HVOCs) from biochar poses a potential threat to both human health and the environment. This study investigates how low pyrolysis temperature (HTT) and the chemical characteristics of lignocellulosi...